Item talk:Q142167

From geokb

{

 "OpenAlex": {
   "id": "https://openalex.org/A5076848145",
   "orcid": "https://orcid.org/0000-0003-2366-1592",
   "display_name": "Josep Antoni Mart\u00edn Fern\u00e1ndez",
   "display_name_alternatives": [
     "Josep Antoni Martin\u2010Fernandex",
     "Josep\u2010Antoni Martin\u2010Fern\u00e1ndez",
     "Josep Antoni Martin\u2010Fern\u00e1ndez",
     "J. Martin\u2010Fernandez",
     "Josep Antoni Mart\u00edn\u2010Fern\u00e1ndez",
     "Josep\u2010Antoni Mart\u00edn\u2010Fern\u00e1ndez",
     "Mart\u00edn Fern\u00e1ndez Jose Antonio",
     "Josep Mart\u00edn\u2010Fern\u00e1ndez",
     "Josep A. Mart\u00edn\u2010Fern\u00e1ndez",
     "J. A. Martin\u2010Fernandez",
     "Josep Antoni Mart\u00edn Fern\u00e1ndez",
     "Josep Antoni Martin\u2010Fernandez",
     "J MARTINFERNANDEZ",
     "J. A. Martin\u2010Fern\u00e1ndez",
     "Josep Fern\u00e1ndez",
     "J. A. Mart\u00edn\u2010Fern\u00e1ndez",
     "J. A. M. Fern\u00e1ndez",
     "Martin"
   ],
   "works_count": 153,
   "cited_by_count": 5337,
   "summary_stats": {
     "2yr_mean_citedness": 2.0714285714285716,
     "h_index": 33,
     "i10_index": 67
   },
   "ids": {
     "openalex": "https://openalex.org/A5076848145",
     "orcid": "https://orcid.org/0000-0003-2366-1592"
   },
   "affiliations": [
     {
       "institution": {
         "id": "https://openalex.org/I251424209",
         "ror": "https://ror.org/01xdxns91",
         "display_name": "University of Girona",
         "country_code": "ES",
         "type": "education",
         "lineage": [
           "https://openalex.org/I251424209"
         ]
       },
       "years": [
         2024,
         2023,
         2022,
         2021,
         2020,
         2019,
         2018,
         2017,
         2016,
         2015
       ]
     },
     {
       "institution": {
         "id": "https://openalex.org/I1286329397",
         "ror": "https://ror.org/035a68863",
         "display_name": "United States Geological Survey",
         "country_code": "US",
         "type": "government",
         "lineage": [
           "https://openalex.org/I1286329397",
           "https://openalex.org/I1335927249"
         ]
       },
       "years": [
         2018
       ]
     },
     {
       "institution": {
         "id": "https://openalex.org/I71267560",
         "ror": "https://ror.org/05290cv24",
         "display_name": "University of Naples Federico II",
         "country_code": "IT",
         "type": "education",
         "lineage": [
           "https://openalex.org/I71267560"
         ]
       },
       "years": [
         2008
       ]
     },
     {
       "institution": {
         "id": "https://openalex.org/I138211613",
         "ror": "https://ror.org/03anc3s24",
         "display_name": "Austrian Academy of Sciences",
         "country_code": "AT",
         "type": "government",
         "lineage": [
           "https://openalex.org/I138211613"
         ]
       },
       "years": [
         2008
       ]
     }
   ],
   "last_known_institutions": [
     {
       "id": "https://openalex.org/I251424209",
       "ror": "https://ror.org/01xdxns91",
       "display_name": "University of Girona",
       "country_code": "ES",
       "type": "education",
       "lineage": [
         "https://openalex.org/I251424209"
       ]
     }
   ],
   "topics": [
     {
       "id": "https://openalex.org/T12157",
       "display_name": "Machine Learning for Mineral Prospectivity Mapping",
       "count": 61,
       "subfield": {
         "id": "https://openalex.org/subfields/1702",
         "display_name": "Artificial Intelligence"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10399",
       "display_name": "Characterization of Shale Gas Pore Structure",
       "count": 19,
       "subfield": {
         "id": "https://openalex.org/subfields/2211",
         "display_name": "Mechanics of Materials"
       },
       "field": {
         "id": "https://openalex.org/fields/22",
         "display_name": "Engineering"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10770",
       "display_name": "Digital Soil Mapping Techniques",
       "count": 14,
       "subfield": {
         "id": "https://openalex.org/subfields/2305",
         "display_name": "Environmental Engineering"
       },
       "field": {
         "id": "https://openalex.org/fields/23",
         "display_name": "Environmental Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10001",
       "display_name": "Tectonic and Geochronological Evolution of Orogens",
       "count": 9,
       "subfield": {
         "id": "https://openalex.org/subfields/1908",
         "display_name": "Geophysics"
       },
       "field": {
         "id": "https://openalex.org/fields/19",
         "display_name": "Earth and Planetary Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11871",
       "display_name": "Detection and Handling of Multicollinearity in Regression Analysis",
       "count": 7,
       "subfield": {
         "id": "https://openalex.org/subfields/2613",
         "display_name": "Statistics and Probability"
       },
       "field": {
         "id": "https://openalex.org/fields/26",
         "display_name": "Mathematics"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10406",
       "display_name": "Exploration and Study of Mars",
       "count": 7,
       "subfield": {
         "id": "https://openalex.org/subfields/3103",
         "display_name": "Astronomy and Astrophysics"
       },
       "field": {
         "id": "https://openalex.org/fields/31",
         "display_name": "Physics and Astronomy"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10325",
       "display_name": "Formation and Evolution of the Solar System",
       "count": 7,
       "subfield": {
         "id": "https://openalex.org/subfields/3103",
         "display_name": "Astronomy and Astrophysics"
       },
       "field": {
         "id": "https://openalex.org/fields/31",
         "display_name": "Physics and Astronomy"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10139",
       "display_name": "Environmental Impact of Heavy Metal Contamination",
       "count": 6,
       "subfield": {
         "id": "https://openalex.org/subfields/2310",
         "display_name": "Pollution"
       },
       "field": {
         "id": "https://openalex.org/fields/23",
         "display_name": "Environmental Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12282",
       "display_name": "Comminution in Mineral Processing",
       "count": 5,
       "subfield": {
         "id": "https://openalex.org/subfields/2210",
         "display_name": "Mechanical Engineering"
       },
       "field": {
         "id": "https://openalex.org/fields/22",
         "display_name": "Engineering"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10866",
       "display_name": "Role of Mediterranean Diet in Health Outcomes",
       "count": 5,
       "subfield": {
         "id": "https://openalex.org/subfields/2739",
         "display_name": "Public Health, Environmental and Occupational Health"
       },
       "field": {
         "id": "https://openalex.org/fields/27",
         "display_name": "Medicine"
       },
       "domain": {
         "id": "https://openalex.org/domains/4",
         "display_name": "Health Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12073",
       "display_name": "Application of Stable Isotopes in Trophic Ecology",
       "count": 5,
       "subfield": {
         "id": "https://openalex.org/subfields/2303",
         "display_name": "Ecology"
       },
       "field": {
         "id": "https://openalex.org/fields/23",
         "display_name": "Environmental Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11063",
       "display_name": "Rough Sets Theory and Applications",
       "count": 4,
       "subfield": {
         "id": "https://openalex.org/subfields/1703",
         "display_name": "Computational Theory and Mathematics"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10836",
       "display_name": "Advances in Metabolomics Research",
       "count": 4,
       "subfield": {
         "id": "https://openalex.org/subfields/1312",
         "display_name": "Molecular Biology"
       },
       "field": {
         "id": "https://openalex.org/fields/13",
         "display_name": "Biochemistry, Genetics and Molecular Biology"
       },
       "domain": {
         "id": "https://openalex.org/domains/1",
         "display_name": "Life Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10010",
       "display_name": "Global Trends in Obesity and Overweight Research",
       "count": 4,
       "subfield": {
         "id": "https://openalex.org/subfields/2739",
         "display_name": "Public Health, Environmental and Occupational Health"
       },
       "field": {
         "id": "https://openalex.org/fields/27",
         "display_name": "Medicine"
       },
       "domain": {
         "id": "https://openalex.org/domains/4",
         "display_name": "Health Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12114",
       "display_name": "Sensory Analysis in Food Science Research",
       "count": 3,
       "subfield": {
         "id": "https://openalex.org/subfields/1106",
         "display_name": "Food Science"
       },
       "field": {
         "id": "https://openalex.org/fields/11",
         "display_name": "Agricultural and Biological Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/1",
         "display_name": "Life Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11854",
       "display_name": "Laser-Induced Breakdown Spectroscopy in Material Analysis",
       "count": 3,
       "subfield": {
         "id": "https://openalex.org/subfields/2211",
         "display_name": "Mechanics of Materials"
       },
       "field": {
         "id": "https://openalex.org/fields/22",
         "display_name": "Engineering"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10211",
       "display_name": "Computational Methods in Drug Discovery",
       "count": 3,
       "subfield": {
         "id": "https://openalex.org/subfields/1703",
         "display_name": "Computational Theory and Mathematics"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T13141",
       "display_name": "Multivariate Analysis in Statistical Research",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/2613",
         "display_name": "Statistics and Probability"
       },
       "field": {
         "id": "https://openalex.org/fields/26",
         "display_name": "Mathematics"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T14406",
       "display_name": "Statistical Analysis in Various Fields",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/1804",
         "display_name": "Statistics, Probability and Uncertainty"
       },
       "field": {
         "id": "https://openalex.org/fields/18",
         "display_name": "Decision Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/2",
         "display_name": "Social Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10637",
       "display_name": "Data Clustering Techniques and Algorithms",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/1702",
         "display_name": "Artificial Intelligence"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10868",
       "display_name": "Design and Control of Soft Robotic Systems",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/2204",
         "display_name": "Biomedical Engineering"
       },
       "field": {
         "id": "https://openalex.org/fields/22",
         "display_name": "Engineering"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10916",
       "display_name": "Surgical Simulation and Training Techniques",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/2746",
         "display_name": "Surgery"
       },
       "field": {
         "id": "https://openalex.org/fields/27",
         "display_name": "Medicine"
       },
       "domain": {
         "id": "https://openalex.org/domains/4",
         "display_name": "Health Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11443",
       "display_name": "Statistical Process Control in Research and Healthcare Improvement",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/1804",
         "display_name": "Statistics, Probability and Uncertainty"
       },
       "field": {
         "id": "https://openalex.org/fields/18",
         "display_name": "Decision Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/2",
         "display_name": "Social Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11901",
       "display_name": "Model-Based Clustering with Mixture Models",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/1702",
         "display_name": "Artificial Intelligence"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T13870",
       "display_name": "Energy, Climate Change, and Environmental Impact Assessment",
       "count": 2,
       "subfield": {
         "id": "https://openalex.org/subfields/2105",
         "display_name": "Renewable Energy, Sustainability and the Environment"
       },
       "field": {
         "id": "https://openalex.org/fields/21",
         "display_name": "Energy"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     }
   ],
   "topic_share": [
     {
       "id": "https://openalex.org/T10770",
       "display_name": "Digital Soil Mapping Techniques",
       "value": 0.0001397,
       "subfield": {
         "id": "https://openalex.org/subfields/2305",
         "display_name": "Environmental Engineering"
       },
       "field": {
         "id": "https://openalex.org/fields/23",
         "display_name": "Environmental Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12157",
       "display_name": "Machine Learning for Mineral Prospectivity Mapping",
       "value": 0.0001381,
       "subfield": {
         "id": "https://openalex.org/subfields/1702",
         "display_name": "Artificial Intelligence"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T13141",
       "display_name": "Multivariate Analysis in Statistical Research",
       "value": 0.0001303,
       "subfield": {
         "id": "https://openalex.org/subfields/2613",
         "display_name": "Statistics and Probability"
       },
       "field": {
         "id": "https://openalex.org/fields/26",
         "display_name": "Mathematics"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T14406",
       "display_name": "Statistical Analysis in Various Fields",
       "value": 0.0001165,
       "subfield": {
         "id": "https://openalex.org/subfields/1804",
         "display_name": "Statistics, Probability and Uncertainty"
       },
       "field": {
         "id": "https://openalex.org/fields/18",
         "display_name": "Decision Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/2",
         "display_name": "Social Sciences"
       }
     },
     {
       "id": "https://openalex.org/T13740",
       "display_name": "Soil Quality Assessment and Management",
       "value": 4.57e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1111",
         "display_name": "Soil Science"
       },
       "field": {
         "id": "https://openalex.org/fields/11",
         "display_name": "Agricultural and Biological Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/1",
         "display_name": "Life Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12114",
       "display_name": "Sensory Analysis in Food Science Research",
       "value": 4.35e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1106",
         "display_name": "Food Science"
       },
       "field": {
         "id": "https://openalex.org/fields/11",
         "display_name": "Agricultural and Biological Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/1",
         "display_name": "Life Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10399",
       "display_name": "Characterization of Shale Gas Pore Structure",
       "value": 4.33e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2211",
         "display_name": "Mechanics of Materials"
       },
       "field": {
         "id": "https://openalex.org/fields/22",
         "display_name": "Engineering"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11871",
       "display_name": "Detection and Handling of Multicollinearity in Regression Analysis",
       "value": 4.33e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2613",
         "display_name": "Statistics and Probability"
       },
       "field": {
         "id": "https://openalex.org/fields/26",
         "display_name": "Mathematics"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10637",
       "display_name": "Data Clustering Techniques and Algorithms",
       "value": 3.97e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1702",
         "display_name": "Artificial Intelligence"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11063",
       "display_name": "Rough Sets Theory and Applications",
       "value": 3.04e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1703",
         "display_name": "Computational Theory and Mathematics"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10139",
       "display_name": "Environmental Impact of Heavy Metal Contamination",
       "value": 3.01e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2310",
         "display_name": "Pollution"
       },
       "field": {
         "id": "https://openalex.org/fields/23",
         "display_name": "Environmental Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12282",
       "display_name": "Comminution in Mineral Processing",
       "value": "3e-05",
       "subfield": {
         "id": "https://openalex.org/subfields/2210",
         "display_name": "Mechanical Engineering"
       },
       "field": {
         "id": "https://openalex.org/fields/22",
         "display_name": "Engineering"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10868",
       "display_name": "Design and Control of Soft Robotic Systems",
       "value": 2.55e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2204",
         "display_name": "Biomedical Engineering"
       },
       "field": {
         "id": "https://openalex.org/fields/22",
         "display_name": "Engineering"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10866",
       "display_name": "Role of Mediterranean Diet in Health Outcomes",
       "value": 2.48e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2739",
         "display_name": "Public Health, Environmental and Occupational Health"
       },
       "field": {
         "id": "https://openalex.org/fields/27",
         "display_name": "Medicine"
       },
       "domain": {
         "id": "https://openalex.org/domains/4",
         "display_name": "Health Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10916",
       "display_name": "Surgical Simulation and Training Techniques",
       "value": 2.35e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2746",
         "display_name": "Surgery"
       },
       "field": {
         "id": "https://openalex.org/fields/27",
         "display_name": "Medicine"
       },
       "domain": {
         "id": "https://openalex.org/domains/4",
         "display_name": "Health Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11443",
       "display_name": "Statistical Process Control in Research and Healthcare Improvement",
       "value": 2.3e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1804",
         "display_name": "Statistics, Probability and Uncertainty"
       },
       "field": {
         "id": "https://openalex.org/fields/18",
         "display_name": "Decision Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/2",
         "display_name": "Social Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12073",
       "display_name": "Application of Stable Isotopes in Trophic Ecology",
       "value": 2.28e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2303",
         "display_name": "Ecology"
       },
       "field": {
         "id": "https://openalex.org/fields/23",
         "display_name": "Environmental Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10406",
       "display_name": "Exploration and Study of Mars",
       "value": 2.05e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/3103",
         "display_name": "Astronomy and Astrophysics"
       },
       "field": {
         "id": "https://openalex.org/fields/31",
         "display_name": "Physics and Astronomy"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12694",
       "display_name": "Language Influence on Cognition and Perception",
       "value": 1.92e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/3205",
         "display_name": "Experimental and Cognitive Psychology"
       },
       "field": {
         "id": "https://openalex.org/fields/32",
         "display_name": "Psychology"
       },
       "domain": {
         "id": "https://openalex.org/domains/2",
         "display_name": "Social Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10001",
       "display_name": "Tectonic and Geochronological Evolution of Orogens",
       "value": 1.87e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1908",
         "display_name": "Geophysics"
       },
       "field": {
         "id": "https://openalex.org/fields/19",
         "display_name": "Earth and Planetary Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11911",
       "display_name": "Spatial Econometrics and Spatial Data Analysis",
       "value": 1.84e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2002",
         "display_name": "Economics and Econometrics"
       },
       "field": {
         "id": "https://openalex.org/fields/20",
         "display_name": "Economics, Econometrics and Finance"
       },
       "domain": {
         "id": "https://openalex.org/domains/2",
         "display_name": "Social Sciences"
       }
     },
     {
       "id": "https://openalex.org/T10836",
       "display_name": "Advances in Metabolomics Research",
       "value": 1.79e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1312",
         "display_name": "Molecular Biology"
       },
       "field": {
         "id": "https://openalex.org/fields/13",
         "display_name": "Biochemistry, Genetics and Molecular Biology"
       },
       "domain": {
         "id": "https://openalex.org/domains/1",
         "display_name": "Life Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12583",
       "display_name": "Food Waste Management and Reduction",
       "value": 1.76e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1106",
         "display_name": "Food Science"
       },
       "field": {
         "id": "https://openalex.org/fields/11",
         "display_name": "Agricultural and Biological Sciences"
       },
       "domain": {
         "id": "https://openalex.org/domains/1",
         "display_name": "Life Sciences"
       }
     },
     {
       "id": "https://openalex.org/T11901",
       "display_name": "Model-Based Clustering with Mixture Models",
       "value": 1.73e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/1702",
         "display_name": "Artificial Intelligence"
       },
       "field": {
         "id": "https://openalex.org/fields/17",
         "display_name": "Computer Science"
       },
       "domain": {
         "id": "https://openalex.org/domains/3",
         "display_name": "Physical Sciences"
       }
     },
     {
       "id": "https://openalex.org/T12920",
       "display_name": "Challenges in Medical Waste Management during COVID-19 Pandemic",
       "value": 1.65e-05,
       "subfield": {
         "id": "https://openalex.org/subfields/2739",
         "display_name": "Public Health, Environmental and Occupational Health"
       },
       "field": {
         "id": "https://openalex.org/fields/27",
         "display_name": "Medicine"
       },
       "domain": {
         "id": "https://openalex.org/domains/4",
         "display_name": "Health Sciences"
       }
     }
   ],
   "x_concepts": [
     {
       "id": "https://openalex.org/C41008148",
       "wikidata": "https://www.wikidata.org/wiki/Q21198",
       "display_name": "Computer science",
       "level": 0,
       "score": 72.5
     },
     {
       "id": "https://openalex.org/C33923547",
       "wikidata": "https://www.wikidata.org/wiki/Q395",
       "display_name": "Mathematics",
       "level": 0,
       "score": 60.8
     },
     {
       "id": "https://openalex.org/C105795698",
       "wikidata": "https://www.wikidata.org/wiki/Q12483",
       "display_name": "Statistics",
       "level": 1,
       "score": 56.2
     },
     {
       "id": "https://openalex.org/C86803240",
       "wikidata": "https://www.wikidata.org/wiki/Q420",
       "display_name": "Biology",
       "level": 0,
       "score": 52.3
     },
     {
       "id": "https://openalex.org/C119857082",
       "wikidata": "https://www.wikidata.org/wiki/Q2539",
       "display_name": "Machine learning",
       "level": 1,
       "score": 43.8
     },
     {
       "id": "https://openalex.org/C121332964",
       "wikidata": "https://www.wikidata.org/wiki/Q413",
       "display_name": "Physics",
       "level": 0,
       "score": 42.5
     },
     {
       "id": "https://openalex.org/C127313418",
       "wikidata": "https://www.wikidata.org/wiki/Q1069",
       "display_name": "Geology",
       "level": 0,
       "score": 37.9
     },
     {
       "id": "https://openalex.org/C138885662",
       "wikidata": "https://www.wikidata.org/wiki/Q5891",
       "display_name": "Philosophy",
       "level": 0,
       "score": 34.6
     },
     {
       "id": "https://openalex.org/C185592680",
       "wikidata": "https://www.wikidata.org/wiki/Q2329",
       "display_name": "Chemistry",
       "level": 0,
       "score": 34.0
     },
     {
       "id": "https://openalex.org/C199360897",
       "wikidata": "https://www.wikidata.org/wiki/Q9143",
       "display_name": "Programming language",
       "level": 1,
       "score": 31.4
     },
     {
       "id": "https://openalex.org/C154945302",
       "wikidata": "https://www.wikidata.org/wiki/Q11660",
       "display_name": "Artificial intelligence",
       "level": 1,
       "score": 30.7
     },
     {
       "id": "https://openalex.org/C2781147490",
       "wikidata": "https://www.wikidata.org/wiki/Q5156808",
       "display_name": "Compositional data",
       "level": 2,
       "score": 29.4
     },
     {
       "id": "https://openalex.org/C127413603",
       "wikidata": "https://www.wikidata.org/wiki/Q11023",
       "display_name": "Engineering",
       "level": 0,
       "score": 24.2
     },
     {
       "id": "https://openalex.org/C162324750",
       "wikidata": "https://www.wikidata.org/wiki/Q8134",
       "display_name": "Economics",
       "level": 0,
       "score": 24.2
     },
     {
       "id": "https://openalex.org/C71924100",
       "wikidata": "https://www.wikidata.org/wiki/Q11190",
       "display_name": "Medicine",
       "level": 0,
       "score": 22.2
     },
     {
       "id": "https://openalex.org/C142362112",
       "wikidata": "https://www.wikidata.org/wiki/Q735",
       "display_name": "Art",
       "level": 0,
       "score": 21.6
     },
     {
       "id": "https://openalex.org/C62520636",
       "wikidata": "https://www.wikidata.org/wiki/Q944",
       "display_name": "Quantum mechanics",
       "level": 1,
       "score": 20.3
     },
     {
       "id": "https://openalex.org/C124101348",
       "wikidata": "https://www.wikidata.org/wiki/Q172491",
       "display_name": "Data mining",
       "level": 1,
       "score": 20.3
     },
     {
       "id": "https://openalex.org/C151730666",
       "wikidata": "https://www.wikidata.org/wiki/Q7205",
       "display_name": "Paleontology",
       "level": 1,
       "score": 20.3
     },
     {
       "id": "https://openalex.org/C205649164",
       "wikidata": "https://www.wikidata.org/wiki/Q1071",
       "display_name": "Geography",
       "level": 0,
       "score": 20.3
     }
   ],
   "counts_by_year": [
     {
       "year": 2024,
       "works_count": 2,
       "cited_by_count": 422
     },
     {
       "year": 2023,
       "works_count": 8,
       "cited_by_count": 673
     },
     {
       "year": 2022,
       "works_count": 6,
       "cited_by_count": 720
     },
     {
       "year": 2021,
       "works_count": 8,
       "cited_by_count": 771
     },
     {
       "year": 2020,
       "works_count": 8,
       "cited_by_count": 623
     },
     {
       "year": 2019,
       "works_count": 5,
       "cited_by_count": 396
     },
     {
       "year": 2018,
       "works_count": 9,
       "cited_by_count": 423
     },
     {
       "year": 2017,
       "works_count": 11,
       "cited_by_count": 197
     },
     {
       "year": 2016,
       "works_count": 9,
       "cited_by_count": 199
     },
     {
       "year": 2015,
       "works_count": 9,
       "cited_by_count": 160
     },
     {
       "year": 2014,
       "works_count": 7,
       "cited_by_count": 143
     },
     {
       "year": 2013,
       "works_count": 6,
       "cited_by_count": 109
     },
     {
       "year": 2012,
       "works_count": 4,
       "cited_by_count": 77
     }
   ],
   "works_api_url": "https://api.openalex.org/works?filter=author.id:A5076848145",
   "updated_date": "2024-08-20T09:58:26.405798",
   "created_date": "2023-07-21",
   "_id": "https://openalex.org/A5076848145"
 },
 "ORCID": {
   "@context": "http://schema.org",
   "@type": "Person",
   "@id": "https://orcid.org/0000-0003-2366-1592",
   "mainEntityOfPage": "https://orcid.org/0000-0003-2366-1592",
   "givenName": "Josep Antoni",
   "familyName": "Mart\u00edn-Fern\u00e1ndez",
   "alternateName": "Martin",
   "@reverse": {
     "creator": [
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.20944/preprints202408.0523.v1",
         "name": "Analysis of Aromatic Fraction of Sparkling Wine Manufactured by Second Fermentation and Aging in Bottle Using Different Types of Closures",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "doi",
           "value": "10.20944/preprints202408.0523.v1"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.3390/math12091388",
         "name": "Lp-Norm for Compositional Data: Exploring the CoDa L1-Norm in Penalised Regression",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "doi",
           "value": "10.3390/math12091388"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11004-023-10115-4",
         "name": "Insights in Hierarchical Clustering of Variables for Compositional Data",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "doi",
           "value": "10.1007/s11004-023-10115-4"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.gexplo.2023.107327",
         "name": "Lasso regression method for a compositional covariate regularised by the norm L1 pairwise logratio",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "doi",
           "value": "10.1016/j.gexplo.2023.107327"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.3390/math11214517",
         "name": "Individualized Prediction of Blood Glucose Outcomes Using Compositional Data Analysis",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "doi",
           "value": "10.3390/math11214517"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.3390/math11051241",
         "name": "Validation of a Probabilistic Prediction Model for Patients with Type 1 Diabetes Using Compositional Data Analysis",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "doi",
           "value": "10.3390/math11051241"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.gexplo.2022.107142",
         "name": "Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85144320803"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.gexplo.2022.107142"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1002/cem.3459",
         "name": "lrSVD: An efficient imputation algorithm for incomplete high\u2010throughput compositional data",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "doi",
           "value": "10.1002/cem.3459"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1002/qre.2910",
         "name": "Measurement, selection, and visualization of association rules: A compositional data perspective",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85105788214"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1002/qre.2910"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.palaeo.2022.110924",
         "name": "High-frequency modification of the central Mediterranean seafloor environment over the last 74 ka",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85126536381"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.palaeo.2022.110924"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1186/s12966-022-01314-z",
         "name": "Intervention effects on children\u2019s movement behaviour accumulation as a result of the\u00a0Transform-Us! school- and home-based cluster randomised controlled trial",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85133578772"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1186/s12966-022-01314-z"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.3390/en15134555",
         "name": "Predicting Rare Earth Element Potential in Produced and Geothermal Waters of the United States via Emergent Self-Organizing Maps",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.3390/en15134555"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85133236300"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.48550/arxiv.2211.01686",
         "name": "Principal Balances of Compositional Data for Regression and Classification using Partial Least Squares",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85141967473"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.48550/arxiv.2211.01686"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.jshs.2021.03.004",
         "name": "Using compositional data analysis to explore accumulation of sedentary behavior, physical activity and youth health",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85106222634"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.jshs.2021.03.004"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11053-020-09659-7",
         "name": "Units Recovery Methods in Compositional Data Analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11053-020-09659-7"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85083373722"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.3390/s21113593",
         "name": "Probabilistic Model of Transition between Categories of Glucose Profiles in Patients with Type 1 Diabetes Using a Compositional Data Analysis Approach",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.3390/s21113593"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85106018422"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/0962280220955221",
         "name": "Analysing body composition as compositional data: An exploration of the relationship between body composition, body mass and bone strength",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/0962280220955221"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85091116119"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.coal.2021.103767",
         "name": "Insights on the characteristics and sources of gas from an underground coal mine using compositional data analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.coal.2021.103767"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85105320200"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s00357-020-09364-3",
         "name": "\u201cCompositional Data Analysis in Practice\u201d by Michael Greenacre Universitat Pompeu Fabra (Barcelona, Spain), Chapman and Hall/CRC, 2018",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s00357-020-09364-3"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85084977275"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.ecolind.2020.106628",
         "name": "Microbial community-level physiological profiles: Considering whole data set and integrating dynamics of colour development",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85087201651"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.ecolind.2020.106628"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.3390/ijerph17072220",
         "name": "Compositional Data Analysis in Time-Use Epidemiology: What, Why, How",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.3390/ijerph17072220"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85082791327"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.26382/amq.2020.02",
         "name": "COMPOSITIONAL REGRESSION-BASED METHODS FOR SST RECONSTRUCTION",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.26382/amq.2020.02"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85098848453"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.jembe.2020.151311",
         "name": "Diet choice in a generalist predator, the invasive lionfish (Pterois volitans/miles)",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85077755766"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.jembe.2020.151311"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.2436/20.8080.02.96",
         "name": "Modelling count data using the logratio-normal-multinomial distribution",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85090124509"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.2436/20.8080.02.96"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11749-019-00672-4",
         "name": "Comments on: Compositional data: the sample space and its structure",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85069215635"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11749-019-00672-4"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s00477-019-01659-1",
         "name": "Advances in self-organizing maps for their application to compositional data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s00477-019-01659-1"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85062605303"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.ifacol.2019.06.194",
         "name": "Compositional data analysis of glucose profiles of type 1 diabetes patients",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.ifacol.2019.06.194"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85070564801"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/1471082x17735919",
         "name": "Merging the components of a finite mixture using posterior probabilities",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85062655064"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/1471082x17735919"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11004-018-9736-z",
         "name": "Compositional Data Analysis of Coal Combustion Products with an Application to a Wyoming Power Plant",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11004-018-9736-z"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85044752655"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000438976800002"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11004-017-9712-z",
         "name": "Advances in Principal Balances for Compositional Data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11004-017-9712-z"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000428252400002"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85034661513"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1186/s12889-018-5207-1",
         "name": "Adiposity and the isotemporal substitution of physical activity, sedentary time and sleep among school-aged children: a compositional data analysis approach",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1186/s12889-018-5207-1"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85042875020"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000427074300006"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/0962280217710835",
         "name": "Compositional data analysis for physical activity, sedentary time and sleep research",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/0962280217710835"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85041863757"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000452307300013"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional data analysis of type 1 diabetes data",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-85051010697"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.gexplo.2018.03.010",
         "name": "Exploratory analysis of multi-element geochemical patterns in soil from the Sarno River Basin (Campania region, southern Italy) through compositional data analysis (CODA)",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.gexplo.2018.03.010"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85044516483"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000450348600010"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11136-018-1791-x",
         "name": "Human development index, children's health-related quality of life and movement behaviors: a compositional data analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11136-018-1791-x"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85040863788"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000432222400007"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/0962280218808819",
         "name": "Individual categorisation of glucose profiles using compositional data analysis.",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/0962280218808819"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "medline:30380996"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85060339077"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.26382/amq.2018.05",
         "name": "Palaeoenvironmental reconstructions through compositional data analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85062641468"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.26382/amq.2018.05"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1111/ijpo.12196",
         "name": "The adiposity of children is associated with their lifestyle behaviours: a cluster analysis of school-aged children from 12 nations",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1111/ijpo.12196"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000419979500005"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85007418103"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/1090198117699508",
         "name": "Academic Performance and Lifestyle Behaviors in Australian School Children: A Cluster Analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000415009800011"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/1090198117699508"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85033441727"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.2139/ssrn.3033588",
         "name": "Association Rules and Compositional Data Analysis: Implications to Big Data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85116408163"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.2139/ssrn.3033588"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.jpeds.2016.12.048",
         "name": "Health-Related Quality of Life and Lifestyle Behavior Clusters in School-Aged Children from 12 Countries",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85009188408"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000400431800035"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.jpeds.2016.12.048"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.wasman.2017.08.036",
         "name": "Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85028662764"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000414818000003"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.wasman.2017.08.036"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/0962280217737805",
         "name": "The compositional isotemporal substitution model: A method for estimating changes in a health outcome for reallocation of time between sleep, physical activity and sedentary behaviour.",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85042110183"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "medline:29157152"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/0962280217737805"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1111/2041-210x.12656",
         "name": "The peril of proportions: robust niche indices for categorical data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000395092500009"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84990205139"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1111/2041-210x.12656"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/1471082x17710398",
         "name": "When relative and absolute information matter: Compositional predictor with a total in generalized linear models",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/1471082x17710398"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000414681000007"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85030572542"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1002/qre.2029",
         "name": "Compositional Data Methods in Customer Survey Analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84976897413"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000384446300012"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1002/qre.2029"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Editorial",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000442588100001"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Log-ratio methods in mixture models for compositional data sets",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000393261500006"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Log-ratio methods in mixture models for compositional data sets",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-85006905977"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.wasman.2016.05.014",
         "name": "Recycling of plastic waste: Presence of phthalates in plastics from households and industry",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84969512872"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.wasman.2016.05.014"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000378962500006"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1080/0740817x.2015.1125042",
         "name": "Signal interpretation in Hotelling's T-2 control chart for compositional data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000379604100007"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84992298349"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1080/0740817x.2015.1125042"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.17713/ajs.v45i4.142",
         "name": "The Mathematics of Compositional Analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.17713/ajs.v45i4.142"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84979775182"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000442588100005"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.pss.2015.04.016",
         "name": "3D-modeling of Mercury's solar wind sputtered surface-exosphere environment",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84938751493"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000360512300012"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.pss.2015.04.016"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1177/1471082x14535524",
         "name": "Bayesian-multiplicative treatment of count zeros in compositional data sets",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1177/1471082x14535524"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84924563397"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000351945300005"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Logratio analysis in archeometry: Principles and methods",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-84988951286"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "On the interpretation of differences between groups for compositional data",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000368469900004"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "On the interpretation of differences between groups for compositional data",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-84953378971"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1515/mper-2015-0018",
         "name": "SOME COMMENTS ON COMPOSITIONAL ANALYSIS IN MANAGEMENT AND PRODUCTION ENGINEERING",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84979574333"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1515/mper-2015-0018"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000219090200008"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11004-014-9529-y",
         "name": "Size Fraction Effects on Planktonic Foraminifera Assemblages: A Compositional Contribution to the Golden Sieve Rush",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84928707526"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11004-014-9529-y"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000353206600005"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.revpalbo.2014.11.004",
         "name": "Vegetation patterns in the Southern Apennines (Italy) during MIS 13: Deciphering pollen variability along a NW-SE transect",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000357232700012"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84988239935"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.revpalbo.2014.11.004"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.chemolab.2015.02.019",
         "name": "zCompositions - R Package for multivariate imputation of left-censored data under a compositional approach",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84924529798"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000353730300009"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.chemolab.2015.02.019"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1002/cem.2621",
         "name": "A bootstrap estimation scheme for chemical compositional data with nondetects",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84904395511"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000340503500006"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1002/cem.2621"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.gexplo.2013.09.003",
         "name": "Compositional methods for estimating elemental concentrations below the limit of detection in practice using R",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84899485992"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.gexplo.2013.09.003"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000336776500007"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Individual T-2 Control Chart for Compositional Data",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000334088200003"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1080/00224065.2014.11917958",
         "name": "Individual T2 control chart for compositional data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-85011079667"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1080/00224065.2014.11917958"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.gexplo.2014.01.014",
         "name": "Methods to investigate the geochemistry of groundwaters with values for nitrogen compounds below the detection limit",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84899479722"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000336776500008"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.gexplo.2014.01.014"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1002/qre.1583",
         "name": "Out-of-Control Signals in Three-Part Compositional T-2 Control Chart",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1002/qre.1583"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000333012500003"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84896393650"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Modelling of weather parameters to predict russet on 'Golden Delicious' apple",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000325385500017"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1080/14620316.2013.11513016",
         "name": "Modelling of weather parameters to predict russet on 'Golden Delicious' apple",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84883421557"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1080/14620316.2013.11513016"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.coal.2012.10.010",
         "name": "Using simulated maps to interpret the geochemistry, formation and quality of the Blue Gem coal bed, Kentucky, USA",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84876476551"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000318832300004"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.coal.2012.10.010"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.aca.2012.12.029",
         "name": "Values below detection limit in compositional chemical data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000315007700004"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.aca.2012.12.029"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84873100116"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s00357-012-9105-4",
         "name": "Dealing with Distances and Transformations for Fuzzy C-Means Clustering of Compositional Data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000305687500003"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s00357-012-9105-4"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84862987859"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.csda.2012.02.012",
         "name": "Model-based replacement of rounded zeros in compositional data: Classical and robust approaches",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.csda.2012.02.012"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84859903807"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000304073600007"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1002/esp.3197",
         "name": "Topographic predictors of susceptibility to alluvial fan flooding, Southern Apennines",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000305511100001"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1002/esp.3197"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-84862656340"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "\u0418\u0421\u0421\u041b\u0415\u0414\u041e\u0412\u0410\u041d\u0418\u0415 \u0413\u0415\u041d\u0415\u0422\u0418\u0427\u0415\u0421\u041a\u0418 \u0420\u0410\u0417\u041b\u0418\u0427\u041d\u042b\u0425 \u041f\u041e\u041b\u0415\u0419 \u0417\u0410\u0413\u0420\u042f\u0417\u041d\u0415\u041d\u0418\u042f \u041e\u0425\u0420\u0410\u041d\u042f\u0415\u041c\u041e\u0419 \u0422\u0415\u0420\u0420\u0418\u0422\u041e\u0420\u0418\u0418: \u0413\u0415\u041e\u0421\u0422\u0410\u0422\u0418\u0421\u0422\u0418\u0427\u0415\u0421\u041a\u0418\u0419 \u0410\u041d\u0410\u041b\u0418\u0417 \u0414\u0410\u041d\u041d\u042b\u0425 \u0411\u0418\u041e\u0418\u041d\u0414\u0418\u041a\u0410\u0426\u0418\u0418",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "source-work-id",
           "value": "0220190812634-154"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional Analysis in Behavioural and Evolutionary Ecology",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-84885548778"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional Data Analysis in Planetology: The Surfaces of Mars And Mercury",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-84885557516"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional Differential Calculus on the Simplex",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-84872402587"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional VARIMA Time Series",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-84866933557"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional VARIMA time series",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000336922300008"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional analysis in behavioural and evolutionary ecology",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000336922300017"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional data analysis in planetology: the surfaces of Mars and Mercury",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000336922300020"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional differential calculus on the simplex",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000336922300014"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Compositional techniques to deal with concentrations below the detection limit in geochemistry,T\u00e9cnicas composicionales para concentraciones geoqu\u00edmicas por debajo del l\u00edmite de detecci\u00f3n",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-80054708203"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Dealing with Zeros",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-80054691956"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Dealing with zeros",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000336922300005"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Elements of Simplicial Linear Algebra and Geometry",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "eid",
           "value": "2-s2.0-84872412884"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Elements of simplicial linear algebra and geometry",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000336922300012"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.cageo.2009.12.011",
         "name": "Gaussian kernels for density estimation with compositional data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.cageo.2009.12.011"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-79955467690"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000291419100008"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1002/jmri.22178",
         "name": "Analysis of New Diffusion Tensor Imaging Anisotropy Measures in the Three-Phase Plot",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000278174300018"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-77952831129"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1002/jmri.22178"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.sedgeo.2010.04.013",
         "name": "Sedimentary chemofacies characterization by means of multivariate analysis",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.sedgeo.2010.04.013"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000280542400010"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-77954214922"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.pss.2010.08.003",
         "name": "Self-consistent modelling of Mercury's exosphere by sputtering, micro-meteorite impact and photon-stimulated desorption",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000283408100008"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.pss.2010.08.003"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-77956609642"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.pss.2010.09.015",
         "name": "Self-consistent modelling of Mercury's exosphere by sputtering, micrometeorite impact and photon-stimulated desorption (vol 58, pg 1599, 2010)",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.pss.2010.09.015"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000285433200029"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-78449276901"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1111/j.1558-5646.2009.00716.x",
         "name": "MAPPING INDIVIDUAL VARIATION IN MALE MATING PREFERENCE SPACE: MULTIPLE CHOICE IN A COLOR POLYMORPHIC CICHLID FISH",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-69249195779"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000269367200016"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1111/j.1558-5646.2009.00716.x"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.cageo.2007.09.015",
         "name": "A modified EM alr-algorithm for replacing rounded zeros in compositional data sets",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000257017400004"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-43649083877"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.cageo.2007.09.015"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "A parametric approach for dealing with compositional rounded zeros",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000250486000001"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11004-007-9100-1",
         "name": "A parametric approach for dealing with compositional rounded zeros",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-35648975472"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11004-007-9100-1"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.icarus.2007.04.034",
         "name": "The lunar exosphere: The sputtering contribution",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000251589500006"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.icarus.2007.04.034"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-35448935938"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1144/gsl.sp.2006.264.01.08",
         "name": "Detailed guide to CoDaPack: A freeware compositional software",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1144/gsl.sp.2006.264.01.08"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-33751004800"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Detailed guide to CoDaPack: a freeware compositional software",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000244484800008"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Major-oxide compositional discrimination in Cenozoic volcanites of Hungary",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000244484800002"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1144/gsl.sp.2006.264.01.02",
         "name": "Major-oxide compositional discrimination in Cenozoic volcanites of Hungary",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1144/gsl.sp.2006.264.01.02"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-33751039095"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1144/gsl.sp.2006.264.01.14",
         "name": "Rounded zeros: Some practical aspects for compositional data",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1144/gsl.sp.2006.264.01.14"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-33751011129"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Rounded zeros: some practical aspects for compositional data",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000244484800014"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1016/j.icarus.2006.01.020",
         "name": "The chemical variability at the surface of Mars: Implication for sediment formation and rock weathering",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1016/j.icarus.2006.01.020"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-33646935228"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000238360400002"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Dealing with compositional data: The freeware CoDaPack",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000233792400007"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11004-005-7379-3",
         "name": "Dealing with compositional data: The freeware CoDaPack",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-33646255470"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11004-005-7379-3"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Subcompositional patterns in Cenozoic volcanic rocks of Hungary",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000233792400005"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1007/s11004-005-7377-5",
         "name": "Subcompositional patterns in Cenozoic volcanic rocks of Hungary",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1007/s11004-005-7377-5"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-33646257571"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1023/a:1023866030544",
         "name": "Dealing with zeros and missing values in compositional data sets using nonparametric imputation",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-0742267880"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1023/a:1023866030544"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "wosuid",
             "value": "wos:000183041900002"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Criteria to compare estimation methods of regionalized compositions",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000172392800001"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1023/a:1012293922142",
         "name": "Criteria to compare estimation methods of regionalized compositions",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-0038249508"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1023/a:1012293922142"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Reply to letter to the editor by S. Rehder and U. Zier on \"Logratio analysis and compositional distance\" by J. Aitchison, C. Barcelo-Vidal, J. A. Martin-Fernandez, and V. Pawlowsky-Glahn",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000171997800005"
         }
       },
       {
         "@type": "CreativeWork",
         "name": "Logratio analysis and compositional distance",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000086212200002"
         }
       },
       {
         "@type": "CreativeWork",
         "@id": "https://doi.org/10.1023/a:1007529726302",
         "name": "Logratio analysis and compositional distance",
         "identifier": [
           {
             "@type": "PropertyValue",
             "propertyID": "eid",
             "value": "2-s2.0-0343130503"
           },
           {
             "@type": "PropertyValue",
             "propertyID": "doi",
             "value": "10.1023/a:1007529726302"
           }
         ]
       },
       {
         "@type": "CreativeWork",
         "name": "Zero replacement in compositional data sets",
         "identifier": {
           "@type": "PropertyValue",
           "propertyID": "wosuid",
           "value": "wos:000166471700025"
         }
       }
     ]
   },
   "url": "http://ima.udg.edu/~jamf/",
   "identifier": [
     {
       "@type": "PropertyValue",
       "propertyID": "ResearcherID",
       "value": "B-9208-2011"
     },
     {
       "@type": "PropertyValue",
       "propertyID": "Scopus Author ID",
       "value": "7004615777"
     }
   ]
 }

}