Item talk:Q314379
From geokb
{
"USGS Publications Warehouse": {
"@context": "https://schema.org",
"@type": "Article",
"additionalType": "Journal Article",
"name": "A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA",
"identifier": [
{
"@type": "PropertyValue",
"propertyID": "USGS Publications Warehouse IndexID",
"value": "70255572",
"url": "https://pubs.usgs.gov/publication/70255572"
},
{
"@type": "PropertyValue",
"propertyID": "USGS Publications Warehouse Internal ID",
"value": 70255572
},
{
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.1016/j.envsoft.2024.106124",
"url": "https://doi.org/10.1016/j.envsoft.2024.106124"
}
],
"journal": {
"@type": "Periodical",
"name": "Environmental Modelling & Software",
"volumeNumber": "179",
"issueNumber": null
},
"inLanguage": "en",
"isPartOf": [
{
"@type": "CreativeWorkSeries",
"name": "Environmental Modelling & Software"
}
],
"datePublished": "2024",
"dateModified": "2024-06-24",
"abstract": "Spatial machine learning models can be developed from observations with substantial unexplainable variability, sometimes called \u2018noise\u2019. Traditional point-scale metrics (e.g., R2) alone can be misleading when evaluating these models. We present a multi-scale performance evaluation (MPE) using two additional scales (distributional and geostatistical). We apply the MPE framework to predictions of depth to bedrock (DTB) in the Delaware River Basin. Geostatistical analysis shows that approximately one third of the DTB variance is at spatial scale smaller than 2\u00a0km. Hence, we interpret our point-scale R2\u00a0of 0.3 (testing data) to be sufficient for regional-scale modelling. Bias-correction methods improve performance at two of the three MPE scales: point-scale change is negligible, while distributional and geostatistical performance improves. In contrast, bias correction applied to a global DTB model does not improve MPE performance. This work encourages scale-appropriate performance evaluations to enable effective model intercomparison.",
"description": "106124, 12 p.",
"publisher": {
"@type": "Organization",
"name": "Elsevier"
},
"author": [
{
"@type": "Person",
"name": "Goodling, Phillip J.",
"givenName": "Phillip J.",
"familyName": "Goodling",
"identifier": {
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0001-5715-8579",
"url": "https://orcid.org/0000-0001-5715-8579"
},
"affiliation": [
{
"@type": "Organization",
"name": "Maryland-Delaware-District of Columbia Water Science Center",
"url": "https://www.usgs.gov/centers/md-de-dc-water"
}
]
},
{
"@type": "Person",
"name": "Stackelberg, Paul",
"givenName": "Paul",
"familyName": "Stackelberg",
"identifier": {
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0002-1818-355X",
"url": "https://orcid.org/0000-0002-1818-355X"
},
"affiliation": [
{
"@type": "Organization",
"name": "National Water Quality Program",
"url": "https://www.usgs.gov/programs/national-water-quality-program"
}
]
},
{
"@type": "Person",
"name": "Fleming, Brandon J. bjflemin@usgs.gov",
"givenName": "Brandon J.",
"familyName": "Fleming",
"email": "bjflemin@usgs.gov",
"identifier": {
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0001-9649-7485",
"url": "https://orcid.org/0000-0001-9649-7485"
},
"affiliation": [
{
"@type": "Organization",
"name": "Maryland Water Science Center",
"url": "https://www.usgs.gov/centers/md-de-dc-water"
}
]
},
{
"@type": "Person",
"name": "Belitz, Kenneth",
"givenName": "Kenneth",
"familyName": "Belitz",
"identifier": {
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0003-4481-2345",
"url": "https://orcid.org/0000-0003-4481-2345"
},
"affiliation": [
{
"@type": "Organization",
"name": "National Water Quality Assessment Program",
"url": "https://www.usgs.gov/programs/national-water-quality-program"
},
{
"@type": "Organization",
"name": "National Water Quality Program",
"url": "https://www.usgs.gov/programs/national-water-quality-program"
},
{
"@type": "Organization",
"name": "WMA - Earth System Processes Division",
"url": "https://www.usgs.gov/mission-areas/water-resources"
},
{
"@type": "Organization",
"name": "New England Water Science Center",
"url": "https://www.usgs.gov/centers/new-england-water-science-center"
},
{
"@type": "Organization",
"name": "Massachusetts Water Science Center",
"url": "https://www.usgs.gov/centers/new-england-water-science-center"
}
]
}
],
"funder": [
{
"@type": "Organization",
"name": "Maryland Water Science Center",
"url": "https://www.usgs.gov/centers/md-de-dc-water"
},
{
"@type": "Organization",
"name": "National Water Quality Program",
"url": "https://www.usgs.gov/programs/national-water-quality-program"
},
{
"@type": "Organization",
"name": "WMA - Earth System Processes Division",
"url": "https://www.usgs.gov/mission-areas/water-resources"
},
{
"@type": "Organization",
"name": "Maryland-Delaware-District of Columbia Water Science Center",
"url": "https://www.usgs.gov/centers/md-de-dc-water"
}
],
"spatialCoverage": [
{
"@type": "Place",
"additionalType": "country",
"name": "United States",
"url": "https://geonames.org/4074035"
},
{
"@type": "Place",
"additionalType": "state",
"name": "Delaware"
},
{
"@type": "Place",
"additionalType": "state",
"name": "New Jersey"
},
{
"@type": "Place",
"additionalType": "state",
"name": "New York"
},
{
"@type": "Place",
"additionalType": "state",
"name": "Pennsylvania"
},
{
"@type": "Place",
"additionalType": "unknown",
"name": "Delaware River basin"
},
{
"@type": "Place",
"geo": [
{
"@type": "GeoShape",
"additionalProperty": {
"@type": "PropertyValue",
"name": "GeoJSON",
"value": {
"type": "FeatureCollection",
"features": [
{
"type": "Feature",
"properties": {},
"geometry": {
"coordinates": [
[
[
-74.88099946089724,
38.58741180591247
],
[
-74.71321333503417,
39.379784628066616
],
[
-74.91854009408658,
39.623906471535875
],
[
-74.56682974019151,
39.83490997578861
],
[
-74.83087158557463,
40.43445755432647
],
[
-74.69462804413362,
42.31099383658801
],
[
-75.89851464683143,
42.243461978517985
],
[
-76.67474108243883,
40.45538711590305
],
[
-76.4341425039691,
39.732367924983954
],
[
-75.81256791410406,
39.70992285882126
],
[
-75.68892404289328,
38.72600697054469
],
[
-74.88099946089724,
38.58741180591247
]
]
],
"type": "Polygon"
}
}
]
}
}
},
{
"@type": "GeoCoordinates",
"latitude": 40.566546284352974,
"longitude": -75.50567186379884
}
]
}
]
},
"OpenAlex": {
"_id": "https://openalex.org/w4399881614",
"abstract_inverted_index": {
"Spatial": [
0
],
"machine": [
1
],
"learning": [
2
],
"models": [
3
],
"can": [
4,
22
],
"be": [
5,
23,
90
],
"developed": [
6
],
"from": [
7
],
"observations": [
8
],
"with": [
9
],
"substantial": [
10
],
"unexplainable": [
11
],
"variability,": [
12
],
"sometimes": [
13
],
"called": [
14
],
"'noise'.": [
15
],
"Traditional": [
16
],
"point-scale": [
17,
83,
106
],
"metrics": [
18
],
"(e.g.,": [
19
],
"R2)": [
20
],
"alone": [
21
],
"misleading": [
24
],
"when": [
25
],
"evaluating": [
26
],
"these": [
27
],
"models.": [
28
],
"We": [
29,
43
],
"present": [
30
],
"a": [
31,
122
],
"multi-scale": [
32
],
"performance": [
33,
98,
114,
135
],
"evaluation": [
34
],
"(MPE)": [
35
],
"using": [
36
],
"two": [
37,
100
],
"additional": [
38
],
"scales": [
39
],
"(distributional": [
40
],
"and": [
41,
112
],
"geostatistical).": [
42
],
"apply": [
44
],
"the": [
45,
56,
68,
102
],
"MPE": [
46,
104,
129
],
"framework": [
47
],
"to": [
48,
52,
89,
121,
137
],
"predictions": [
49
],
"of": [
50,
67,
85,
101
],
"depth": [
51
],
"bedrock": [
53
],
"(DTB)": [
54
],
"in": [
55
],
"Delaware": [
57
],
"River": [
58
],
"Basin.": [
59
],
"Geostatistical": [
60
],
"analysis": [
61
],
"shows": [
62
],
"that": [
63
],
"approximately": [
64
],
"one": [
65
],
"third": [
66
],
"DTB": [
69,
124
],
"variance": [
70
],
"is": [
71,
108
],
"at": [
72,
99
],
"spatial": [
73
],
"scale": [
74
],
"smaller": [
75
],
"than": [
76
],
"2": [
77
],
"km.": [
78
],
"Hence,": [
79
],
"we": [
80
],
"interpret": [
81
],
"our": [
82
],
"R2": [
84
],
"0.3": [
86
],
"(testing": [
87
],
"data)": [
88
],
"sufficient": [
91
],
"for": [
92
],
"regional-scale": [
93
],
"modelling.": [
94
],
"Bias-correction": [
95
],
"methods": [
96
],
"improve": [
97,
128
],
"three": [
103
],
"scales:": [
105
],
"change": [
107
],
"negligible,": [
109
],
"while": [
110
],
"distributional": [
111
],
"geostatistical": [
113
],
"improves.": [
115
],
"In": [
116
],
"contrast,": [
117
],
"bias": [
118
],
"correction": [
119
],
"applied": [
120
],
"global": [
123
],
"model": [
125,
140
],
"does": [
126
],
"not": [
127
],
"performance.": [
130
],
"This": [
131
],
"work": [
132
],
"encourages": [
133
],
"scale-appropriate": [
134
],
"evaluations": [
136
],
"enable": [
138
],
"effective": [
139
],
"intercomparison.": [
141
]
},
"apc_list": {
"value": 3400,
"currency": "USD",
"value_usd": 3400,
"provenance": "doaj"
},
"apc_paid": {
"value": 3400,
"currency": "USD",
"value_usd": 3400,
"provenance": "doaj"
},
"authorships": [
{
"author_position": "first",
"author": {
"id": "https://openalex.org/A5012731036",
"display_name": "Phillip Goodling",
"orcid": "https://orcid.org/0000-0001-5715-8579"
},
"institutions": [
{
"id": "https://openalex.org/I1286329397",
"display_name": "United States Geological Survey",
"ror": "https://ror.org/035a68863",
"country_code": "US",
"type": "government",
"lineage": [
"https://openalex.org/I1286329397",
"https://openalex.org/I1335927249"
]
}
],
"countries": [
"US"
],
"is_corresponding": true,
"raw_author_name": "P. Goodling",
"raw_affiliation_strings": [
"U.S. Geological Survey, 5522 Research Park Drive, Catonsville, MD, 21228, USA"
],
"affiliations": [
{
"raw_affiliation_string": "U.S. Geological Survey, 5522 Research Park Drive, Catonsville, MD, 21228, USA",
"institution_ids": [
"https://openalex.org/I1286329397"
]
}
]
},
{
"author_position": "middle",
"author": {
"id": "https://openalex.org/A5033970817",
"display_name": "Kenneth Belitz",
"orcid": "https://orcid.org/0000-0003-4481-2345"
},
"institutions": [
{
"id": "https://openalex.org/I1286329397",
"display_name": "United States Geological Survey",
"ror": "https://ror.org/035a68863",
"country_code": "US",
"type": "government",
"lineage": [
"https://openalex.org/I1286329397",
"https://openalex.org/I1335927249"
]
}
],
"countries": [
"US"
],
"is_corresponding": false,
"raw_author_name": "K. Belitz",
"raw_affiliation_strings": [
"U.S. Geological Survey, 10 Bearfoot Road, Northborough, MA, 01532, USA"
],
"affiliations": [
{
"raw_affiliation_string": "U.S. Geological Survey, 10 Bearfoot Road, Northborough, MA, 01532, USA",
"institution_ids": [
"https://openalex.org/I1286329397"
]
}
]
},
{
"author_position": "middle",
"author": {
"id": "https://openalex.org/A5001031625",
"display_name": "Paul E. Stackelberg",
"orcid": "https://orcid.org/0000-0002-1818-355X"
},
"institutions": [
{
"id": "https://openalex.org/I1286329397",
"display_name": "United States Geological Survey",
"ror": "https://ror.org/035a68863",
"country_code": "US",
"type": "government",
"lineage": [
"https://openalex.org/I1286329397",
"https://openalex.org/I1335927249"
]
}
],
"countries": [
"US"
],
"is_corresponding": false,
"raw_author_name": "P. Stackelberg",
"raw_affiliation_strings": [
"U.S. Geological Survey, 425 Jordan Road, Troy, NY, 12180, USA"
],
"affiliations": [
{
"raw_affiliation_string": "U.S. Geological Survey, 425 Jordan Road, Troy, NY, 12180, USA",
"institution_ids": [
"https://openalex.org/I1286329397"
]
}
]
},
{
"author_position": "last",
"author": {
"id": "https://openalex.org/A5010258663",
"display_name": "Braden C. Fleming",
"orcid": "https://orcid.org/0000-0002-7841-425X"
},
"institutions": [
{
"id": "https://openalex.org/I1286329397",
"display_name": "United States Geological Survey",
"ror": "https://ror.org/035a68863",
"country_code": "US",
"type": "government",
"lineage": [
"https://openalex.org/I1286329397",
"https://openalex.org/I1335927249"
]
}
],
"countries": [
"US"
],
"is_corresponding": false,
"raw_author_name": "B. Fleming",
"raw_affiliation_strings": [
"U.S. Geological Survey, 215 Limekiln Rd, New Cumberland, PA, 17010, USA"
],
"affiliations": [
{
"raw_affiliation_string": "U.S. Geological Survey, 215 Limekiln Rd, New Cumberland, PA, 17010, USA",
"institution_ids": [
"https://openalex.org/I1286329397"
]
}
]
}
],
"best_oa_location": {
"is_oa": true,
"landing_page_url": "https://doi.org/10.1016/j.envsoft.2024.106124",
"pdf_url": null,
"source": {
"id": "https://openalex.org/S113611870",
"display_name": "Environmental Modelling & Software",
"issn_l": "1364-8152",
"issn": [
"1364-8152",
"1873-6726"
],
"is_oa": false,
"is_in_doaj": false,
"is_core": true,
"host_organization": "https://openalex.org/P4310320990",
"host_organization_name": "Elsevier BV",
"host_organization_lineage": [
"https://openalex.org/P4310320990"
],
"host_organization_lineage_names": [
"Elsevier BV"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
},
"biblio": {
"volume": null,
"issue": null,
"first_page": "106124",
"last_page": "106124"
},
"citation_normalized_percentile": null,
"cited_by_api_url": "https://api.openalex.org/works?filter=cites:W4399881614",
"cited_by_count": 0,
"cited_by_percentile_year": {
"min": 0,
"max": 88
},
"concepts": [
{
"id": "https://openalex.org/C137527640",
"wikidata": "https://www.wikidata.org/wiki/Q570309",
"display_name": "Bedrock",
"level": 2,
"score": 0.87255615
},
{
"id": "https://openalex.org/C109007969",
"wikidata": "https://www.wikidata.org/wiki/Q749565",
"display_name": "Structural basin",
"level": 2,
"score": 0.6158834
},
{
"id": "https://openalex.org/C127313418",
"wikidata": "https://www.wikidata.org/wiki/Q1069",
"display_name": "Geology",
"level": 0,
"score": 0.49778318
},
{
"id": "https://openalex.org/C119857082",
"wikidata": "https://www.wikidata.org/wiki/Q2539",
"display_name": "Machine learning",
"level": 1,
"score": 0.42324966
},
{
"id": "https://openalex.org/C41008148",
"wikidata": "https://www.wikidata.org/wiki/Q21198",
"display_name": "Computer science",
"level": 0,
"score": 0.41034573
},
{
"id": "https://openalex.org/C154945302",
"wikidata": "https://www.wikidata.org/wiki/Q11660",
"display_name": "Artificial intelligence",
"level": 1,
"score": 0.40448955
},
{
"id": "https://openalex.org/C124101348",
"wikidata": "https://www.wikidata.org/wiki/Q172491",
"display_name": "Data mining",
"level": 1,
"score": 0.33284152
},
{
"id": "https://openalex.org/C114793014",
"wikidata": "https://www.wikidata.org/wiki/Q52109",
"display_name": "Geomorphology",
"level": 1,
"score": 0.23481748
}
],
"corresponding_author_ids": [
"https://openalex.org/A5012731036"
],
"corresponding_institution_ids": [
"https://openalex.org/I1286329397"
],
"countries_distinct_count": 1,
"counts_by_year": [],
"created_date": "2024-06-22",
"datasets": [],
"display_name": "A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA",
"doi": "https://doi.org/10.1016/j.envsoft.2024.106124",
"fwci": 0.0,
"grants": [
{
"funder": "https://openalex.org/F4320332183",
"funder_display_name": "U.S. Geological Survey",
"award_id": null
}
],
"has_fulltext": false,
"id": "https://openalex.org/W4399881614",
"ids": {
"openalex": "https://openalex.org/W4399881614",
"doi": "https://doi.org/10.1016/j.envsoft.2024.106124"
},
"indexed_in": [
"crossref"
],
"institutions_distinct_count": 1,
"is_paratext": false,
"is_retracted": false,
"keywords": [
{
"id": "https://openalex.org/keywords/bedrock",
"display_name": "Bedrock",
"score": 0.87255615
},
{
"id": "https://openalex.org/keywords/watershed-simulation",
"display_name": "Watershed Simulation",
"score": 0.563044
},
{
"id": "https://openalex.org/keywords/terrain-analysis",
"display_name": "Terrain Analysis",
"score": 0.55552
},
{
"id": "https://openalex.org/keywords/hydrological-modeling",
"display_name": "Hydrological Modeling",
"score": 0.551187
},
{
"id": "https://openalex.org/keywords/model-evaluation",
"display_name": "Model Evaluation",
"score": 0.530043
},
{
"id": "https://openalex.org/keywords/compositional-data-analysis",
"display_name": "Compositional Data Analysis",
"score": 0.52905
}
],
"language": "en",
"locations": [
{
"is_oa": true,
"landing_page_url": "https://doi.org/10.1016/j.envsoft.2024.106124",
"pdf_url": null,
"source": {
"id": "https://openalex.org/S113611870",
"display_name": "Environmental Modelling & Software",
"issn_l": "1364-8152",
"issn": [
"1364-8152",
"1873-6726"
],
"is_oa": false,
"is_in_doaj": false,
"is_core": true,
"host_organization": "https://openalex.org/P4310320990",
"host_organization_name": "Elsevier BV",
"host_organization_lineage": [
"https://openalex.org/P4310320990"
],
"host_organization_lineage_names": [
"Elsevier BV"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
}
],
"locations_count": 1,
"mesh": [],
"ngrams_url": "https://api.openalex.org/works/W4399881614/ngrams",
"open_access": {
"is_oa": true,
"oa_status": "hybrid",
"oa_url": "https://doi.org/10.1016/j.envsoft.2024.106124",
"any_repository_has_fulltext": false
},
"primary_location": {
"is_oa": true,
"landing_page_url": "https://doi.org/10.1016/j.envsoft.2024.106124",
"pdf_url": null,
"source": {
"id": "https://openalex.org/S113611870",
"display_name": "Environmental Modelling & Software",
"issn_l": "1364-8152",
"issn": [
"1364-8152",
"1873-6726"
],
"is_oa": false,
"is_in_doaj": false,
"is_core": true,
"host_organization": "https://openalex.org/P4310320990",
"host_organization_name": "Elsevier BV",
"host_organization_lineage": [
"https://openalex.org/P4310320990"
],
"host_organization_lineage_names": [
"Elsevier BV"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
},
"primary_topic": {
"id": "https://openalex.org/T10770",
"display_name": "Digital Soil Mapping Techniques",
"score": 0.9997,
"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"
}
},
"publication_date": "2024-06-01",
"publication_year": 2024,
"referenced_works": [
"https://openalex.org/W2007873570",
"https://openalex.org/W2024697317",
"https://openalex.org/W2091259694",
"https://openalex.org/W2130089609",
"https://openalex.org/W2144064225",
"https://openalex.org/W2199578048",
"https://openalex.org/W2560720403",
"https://openalex.org/W2564901692",
"https://openalex.org/W2567805992",
"https://openalex.org/W2606716674",
"https://openalex.org/W2613126452",
"https://openalex.org/W2763313479",
"https://openalex.org/W2773188111",
"https://openalex.org/W2785044143",
"https://openalex.org/W2790000326",
"https://openalex.org/W2793997912",
"https://openalex.org/W2798064106",
"https://openalex.org/W2885995093",
"https://openalex.org/W2896139965",
"https://openalex.org/W2899087191",
"https://openalex.org/W2900710900",
"https://openalex.org/W2912539592",
"https://openalex.org/W2980948052",
"https://openalex.org/W2995353642",
"https://openalex.org/W3027312415",
"https://openalex.org/W3086056576",
"https://openalex.org/W3102027041",
"https://openalex.org/W3130306759",
"https://openalex.org/W3148789799",
"https://openalex.org/W3177746823",
"https://openalex.org/W3206624927",
"https://openalex.org/W4213279137",
"https://openalex.org/W4225565691",
"https://openalex.org/W4229048457",
"https://openalex.org/W429766147",
"https://openalex.org/W4307956187"
],
"referenced_works_count": 36,
"related_works": [
"https://openalex.org/W4394896187",
"https://openalex.org/W4386462264",
"https://openalex.org/W4364306694",
"https://openalex.org/W4312192474",
"https://openalex.org/W4306674287",
"https://openalex.org/W4283697347",
"https://openalex.org/W3170094116",
"https://openalex.org/W3107602296",
"https://openalex.org/W3046775127",
"https://openalex.org/W2961085424"
],
"sustainable_development_goals": [
{
"id": "https://metadata.un.org/sdg/13",
"display_name": "Climate action",
"score": 0.61
}
],
"title": "A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA",
"topics": [
{
"id": "https://openalex.org/T10770",
"display_name": "Digital Soil Mapping Techniques",
"score": 0.9997,
"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",
"score": 0.9946,
"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/T10330",
"display_name": "Hydrological Modeling and Water Resource Management",
"score": 0.9877,
"subfield": {
"id": "https://openalex.org/subfields/2312",
"display_name": "Water Science and Technology"
},
"field": {
"id": "https://openalex.org/fields/23",
"display_name": "Environmental Science"
},
"domain": {
"id": "https://openalex.org/domains/3",
"display_name": "Physical Sciences"
}
}
],
"type": "article",
"type_crossref": "journal-article",
"updated_date": "2024-08-11T10:23:38.960759",
"versions": []
}
}
