Item talk:Q303346
From geokb
{
"USGS Publications Warehouse": {
"@context": "https://schema.org",
"@type": "Article",
"additionalType": "Journal Article",
"name": "Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions",
"identifier": [
{
"@type": "PropertyValue",
"propertyID": "USGS Publications Warehouse IndexID",
"value": "70251245",
"url": "https://pubs.usgs.gov/publication/70251245"
},
{
"@type": "PropertyValue",
"propertyID": "USGS Publications Warehouse Internal ID",
"value": 70251245
},
{
"@type": "PropertyValue",
"propertyID": "DOI",
"value": "10.1111/cobi.14203",
"url": "https://doi.org/10.1111/cobi.14203"
}
],
"journal": {
"@type": "Periodical",
"name": "Conservation Biology",
"volumeNumber": "38",
"issueNumber": "2"
},
"inLanguage": "en",
"isPartOf": [
{
"@type": "CreativeWorkSeries",
"name": "Conservation Biology"
}
],
"datePublished": "2024",
"dateModified": "2024-06-03",
"abstract": "Ecosystem state transitions can be ecologically devastating or be a restoration success. State transitions are common within aquatic systems worldwide, especially considering human-mediated changes to land use and water use. We created a transferable conceptual framework to enable multiscale assessments of state resilience and early warnings of state transitions that can inform strategic restorations and avoid ecosystem collapse. The conceptual framework integrated machine learning predictions with ecosystem state concepts (e.g., state classification, gradients of vulnerability, and recovery potential leading to state transitions) and was devised to investigate possible environmental drivers. As an application of the framework, we generated prediction probabilities of submersed aquatic vegetation (SAV) presence at nearly 10,000 sites in the Upper Mississippi River (United States). Then, we used an interpretability method to explain model predictions to gain insights into possible environmental drivers and thresholds or linear responses of SAV presence and absence. Model accuracy was 89% without spatial bias. Average water depth, suspended solids, substrate, and distance to nearest SAV were the best predictors and likely environmental drivers of SAV habitat suitability. These environmental drivers exhibited nonlinear, threshold-type responses for SAV. All the results are also presented in an online dashboard to explore results at many spatial scales. The habitat suitability model outputs and prediction explanations from many spatial scales (4\u00a0m to 400\u00a0km of river reach) can inform research and restoration planning.",
"description": "e14203, 13 p.",
"publisher": {
"@type": "Organization",
"name": "Wiley"
},
"author": [
{
"@type": "Person",
"name": "Larson, Danelle M.",
"givenName": "Danelle M.",
"familyName": "Larson",
"identifier": {
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0001-6349-6267",
"url": "https://orcid.org/0000-0001-6349-6267"
},
"affiliation": [
{
"@type": "Organization",
"name": "Upper Midwest Environmental Sciences Center",
"url": "https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center"
}
]
},
{
"@type": "Person",
"name": "Delaney, John T.",
"givenName": "John T.",
"familyName": "Delaney",
"identifier": {
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0003-1038-0265",
"url": "https://orcid.org/0000-0003-1038-0265"
},
"affiliation": [
{
"@type": "Organization",
"name": "Upper Midwest Environmental Sciences Center",
"url": "https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center"
}
]
}
],
"funder": [
{
"@type": "Organization",
"name": "Upper Midwest Environmental Sciences Center",
"url": "https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center"
}
]
},
"OpenAlex": {
"_id": "https://openalex.org/w4387516284",
"abstract_inverted_index": {
"Abstract": [
0
],
"Ecosystem": [
1
],
"state": [
2,
42,
48,
68,
71,
81
],
"transitions": [
3,
14,
49
],
"can": [
4,
51,
221
],
"be": [
5,
9
],
"ecologically": [
6
],
"devastating": [
7
],
"or": [
8,
137
],
"a": [
10,
33
],
"restoration": [
11,
225
],
"success.": [
12
],
"State": [
13
],
"are": [
15,
187
],
"common": [
16
],
"within": [
17
],
"aquatic": [
18,
103
],
"systems": [
19
],
"worldwide,": [
20
],
"especially": [
21
],
"considering": [
22
],
"human\u2010mediated": [
23
],
"changes": [
24
],
"to": [
25,
37,
80,
86,
124,
128,
160,
194,
215
],
"land": [
26
],
"use": [
27
],
"and": [
28,
44,
55,
76,
83,
135,
143,
158,
167,
206,
224
],
"water": [
29,
153
],
"use.": [
30
],
"We": [
31
],
"created": [
32
],
"transferable": [
34
],
"conceptual": [
35,
60
],
"framework": [
36,
61
],
"enable": [
38
],
"multiscale": [
39
],
"assessments": [
40
],
"of": [
41,
47,
74,
94,
101,
140,
171,
218
],
"resilience": [
43
],
"early": [
45
],
"warnings": [
46
],
"that": [
50
],
"inform": [
52,
222
],
"strategic": [
53
],
"restorations": [
54
],
"avoid": [
56
],
"ecosystem": [
57,
67
],
"collapse.": [
58
],
"The": [
59,
201
],
"integrated": [
62
],
"machine": [
63
],
"learning": [
64
],
"predictions": [
65,
127
],
"with": [
66
],
"concepts": [
69
],
"(e.g.,": [
70
],
"classification,": [
72
],
"gradients": [
73
],
"vulnerability,": [
75
],
"recovery": [
77
],
"potential": [
78
],
"leading": [
79
],
"transitions)": [
82
],
"was": [
84,
147
],
"devised": [
85
],
"investigate": [
87
],
"possible": [
88,
132
],
"environmental": [
89,
133,
169,
176
],
"drivers.": [
90
],
"As": [
91
],
"an": [
92,
121,
191
],
"application": [
93
],
"the": [
95,
112,
164,
185
],
"framework,": [
96
],
"we": [
97,
119
],
"generated": [
98
],
"prediction": [
99,
207
],
"probabilities": [
100
],
"submersed": [
102
],
"vegetation": [
104
],
"(SAV)": [
105
],
"presence": [
106,
142
],
"at": [
107,
197
],
"nearly": [
108
],
"10,000": [
109
],
"sites": [
110
],
"in": [
111,
190
],
"Upper": [
113
],
"Mississippi": [
114
],
"River": [
115
],
"(United": [
116
],
"States).": [
117
],
"Then,": [
118
],
"used": [
120
],
"interpretability": [
122
],
"method": [
123
],
"explain": [
125
],
"model": [
126,
204
],
"gain": [
129
],
"insights": [
130
],
"into": [
131
],
"drivers": [
134,
170,
177
],
"thresholds": [
136
],
"linear": [
138
],
"responses": [
139,
181
],
"SAV": [
141,
162,
172
],
"absence.": [
144
],
"Model": [
145
],
"accuracy": [
146
],
"89%": [
148
],
"without": [
149
],
"spatial": [
150,
199,
211
],
"bias.": [
151
],
"Average": [
152
],
"depth,": [
154
],
"suspended": [
155
],
"solids,": [
156
],
"substrate,": [
157
],
"distance": [
159
],
"nearest": [
161
],
"were": [
163
],
"best": [
165
],
"predictors": [
166
],
"likely": [
168
],
"habitat": [
173,
202
],
"suitability.": [
174
],
"These": [
175
],
"exhibited": [
178
],
"nonlinear,": [
179
],
"threshold\u2010type": [
180
],
"for": [
182
],
"SAV.": [
183
],
"All": [
184
],
"results": [
186,
196
],
"also": [
188
],
"presented": [
189
],
"online": [
192
],
"dashboard": [
193
],
"explore": [
195
],
"many": [
198,
210
],
"scales.": [
200
],
"suitability": [
203
],
"outputs": [
205
],
"explanations": [
208
],
"from": [
209
],
"scales": [
212
],
"(4": [
213
],
"m": [
214
],
"400": [
216
],
"km": [
217
],
"river": [
219
],
"reach)": [
220
],
"research": [
223
],
"planning.": [
226
]
},
"apc_list": {
"value": 3090,
"currency": "USD",
"value_usd": 3090,
"provenance": "doaj"
},
"apc_paid": {
"value": 3090,
"currency": "USD",
"value_usd": 3090,
"provenance": "doaj"
},
"authorships": [
{
"author_position": "first",
"author": {
"id": "https://openalex.org/A5009185440",
"display_name": "John Thomas Delaney",
"orcid": "https://orcid.org/0000-0003-1038-0265"
},
"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": "John T. Delaney",
"raw_affiliation_strings": [
"U.S. Geological Survey, La Crosse, Wisconsin, USA"
],
"affiliations": [
{
"raw_affiliation_string": "U.S. Geological Survey, La Crosse, Wisconsin, USA",
"institution_ids": [
"https://openalex.org/I1286329397"
]
}
]
},
{
"author_position": "last",
"author": {
"id": "https://openalex.org/A5048214452",
"display_name": "Danelle M. Larson",
"orcid": "https://orcid.org/0000-0001-6349-6267"
},
"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": "Danelle M. Larson",
"raw_affiliation_strings": [
"U.S. Geological Survey, La Crosse, Wisconsin, USA"
],
"affiliations": [
{
"raw_affiliation_string": "U.S. Geological Survey, La Crosse, Wisconsin, USA",
"institution_ids": [
"https://openalex.org/I1286329397"
]
}
]
}
],
"best_oa_location": {
"is_oa": true,
"landing_page_url": "https://doi.org/10.1111/cobi.14203",
"pdf_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cobi.14203",
"source": {
"id": "https://openalex.org/S98137347",
"display_name": "Conservation Biology",
"issn_l": "0888-8892",
"issn": [
"0888-8892",
"1523-1739"
],
"is_oa": false,
"is_in_doaj": false,
"is_core": true,
"host_organization": "https://openalex.org/P4310320595",
"host_organization_name": "Wiley",
"host_organization_lineage": [
"https://openalex.org/P4310320595"
],
"host_organization_lineage_names": [
"Wiley"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
},
"biblio": {
"volume": "38",
"issue": "3",
"first_page": null,
"last_page": null
},
"citation_normalized_percentile": {
"value": 0.999886,
"is_in_top_1_percent": true,
"is_in_top_10_percent": true
},
"cited_by_api_url": "https://api.openalex.org/works?filter=cites:W4387516284",
"cited_by_count": 1,
"cited_by_percentile_year": {
"min": 88,
"max": 95
},
"concepts": [
{
"id": "https://openalex.org/C2781067378",
"wikidata": "https://www.wikidata.org/wiki/Q17027399",
"display_name": "Interpretability",
"level": 2,
"score": 0.6655848
},
{
"id": "https://openalex.org/C107826830",
"wikidata": "https://www.wikidata.org/wiki/Q929380",
"display_name": "Environmental resource management",
"level": 1,
"score": 0.6170289
},
{
"id": "https://openalex.org/C95713431",
"wikidata": "https://www.wikidata.org/wiki/Q631425",
"display_name": "Vulnerability (computing)",
"level": 2,
"score": 0.60230577
},
{
"id": "https://openalex.org/C2779585090",
"wikidata": "https://www.wikidata.org/wiki/Q3457762",
"display_name": "Resilience (materials science)",
"level": 2,
"score": 0.5764269
},
{
"id": "https://openalex.org/C110872660",
"wikidata": "https://www.wikidata.org/wiki/Q37813",
"display_name": "Ecosystem",
"level": 2,
"score": 0.5700266
},
{
"id": "https://openalex.org/C12064787",
"wikidata": "https://www.wikidata.org/wiki/Q4736552",
"display_name": "Alternative stable state",
"level": 3,
"score": 0.5057633
},
{
"id": "https://openalex.org/C58941895",
"wikidata": "https://www.wikidata.org/wiki/Q295865",
"display_name": "Ecosystem services",
"level": 3,
"score": 0.49408725
},
{
"id": "https://openalex.org/C137176749",
"wikidata": "https://www.wikidata.org/wiki/Q4105337",
"display_name": "Psychological resilience",
"level": 2,
"score": 0.4710184
},
{
"id": "https://openalex.org/C48103436",
"wikidata": "https://www.wikidata.org/wiki/Q599031",
"display_name": "State (computer science)",
"level": 2,
"score": 0.4559702
},
{
"id": "https://openalex.org/C39432304",
"wikidata": "https://www.wikidata.org/wiki/Q188847",
"display_name": "Environmental science",
"level": 0,
"score": 0.44349733
},
{
"id": "https://openalex.org/C78437154",
"wikidata": "https://www.wikidata.org/wiki/Q2428433",
"display_name": "Restoration ecology",
"level": 2,
"score": 0.4349832
},
{
"id": "https://openalex.org/C41008148",
"wikidata": "https://www.wikidata.org/wiki/Q21198",
"display_name": "Computer science",
"level": 0,
"score": 0.43142465
},
{
"id": "https://openalex.org/C175327387",
"wikidata": "https://www.wikidata.org/wiki/Q3289906",
"display_name": "Aquatic ecosystem",
"level": 2,
"score": 0.41555858
},
{
"id": "https://openalex.org/C18903297",
"wikidata": "https://www.wikidata.org/wiki/Q7150",
"display_name": "Ecology",
"level": 1,
"score": 0.35427076
},
{
"id": "https://openalex.org/C154945302",
"wikidata": "https://www.wikidata.org/wiki/Q11660",
"display_name": "Artificial intelligence",
"level": 1,
"score": 0.19954628
},
{
"id": "https://openalex.org/C15744967",
"wikidata": "https://www.wikidata.org/wiki/Q9418",
"display_name": "Psychology",
"level": 0,
"score": 0.0
},
{
"id": "https://openalex.org/C121332964",
"wikidata": "https://www.wikidata.org/wiki/Q413",
"display_name": "Physics",
"level": 0,
"score": 0.0
},
{
"id": "https://openalex.org/C38652104",
"wikidata": "https://www.wikidata.org/wiki/Q3510521",
"display_name": "Computer security",
"level": 1,
"score": 0.0
},
{
"id": "https://openalex.org/C11413529",
"wikidata": "https://www.wikidata.org/wiki/Q8366",
"display_name": "Algorithm",
"level": 1,
"score": 0.0
},
{
"id": "https://openalex.org/C86803240",
"wikidata": "https://www.wikidata.org/wiki/Q420",
"display_name": "Biology",
"level": 0,
"score": 0.0
},
{
"id": "https://openalex.org/C542102704",
"wikidata": "https://www.wikidata.org/wiki/Q183257",
"display_name": "Psychotherapist",
"level": 1,
"score": 0.0
},
{
"id": "https://openalex.org/C97355855",
"wikidata": "https://www.wikidata.org/wiki/Q11473",
"display_name": "Thermodynamics",
"level": 1,
"score": 0.0
}
],
"corresponding_author_ids": [
"https://openalex.org/A5048214452"
],
"corresponding_institution_ids": [
"https://openalex.org/I1286329397"
],
"countries_distinct_count": 1,
"counts_by_year": [
{
"year": 2024,
"cited_by_count": 1
}
],
"created_date": "2023-10-12",
"datasets": [],
"display_name": "Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions",
"doi": "https://doi.org/10.1111/cobi.14203",
"fwci": 2.379,
"grants": [],
"has_fulltext": false,
"id": "https://openalex.org/W4387516284",
"ids": {
"openalex": "https://openalex.org/W4387516284",
"doi": "https://doi.org/10.1111/cobi.14203",
"pmid": "https://pubmed.ncbi.nlm.nih.gov/37817744"
},
"indexed_in": [
"crossref",
"pubmed"
],
"institutions_distinct_count": 1,
"is_paratext": false,
"is_retracted": false,
"keywords": [
{
"id": "https://openalex.org/keywords/interpretability",
"display_name": "Interpretability",
"score": 0.6655848
},
{
"id": "https://openalex.org/keywords/vulnerability",
"display_name": "Vulnerability (computing)",
"score": 0.60230577
},
{
"id": "https://openalex.org/keywords/resilience",
"display_name": "Resilience (materials science)",
"score": 0.5764269
},
{
"id": "https://openalex.org/keywords/model-evaluation",
"display_name": "Model Evaluation",
"score": 0.535515
},
{
"id": "https://openalex.org/keywords/machine-learning",
"display_name": "Machine Learning",
"score": 0.533284
},
{
"id": "https://openalex.org/keywords/statistical-modeling",
"display_name": "Statistical Modeling",
"score": 0.514186
},
{
"id": "https://openalex.org/keywords/alternative-stable-state",
"display_name": "Alternative stable state",
"score": 0.5057633
},
{
"id": "https://openalex.org/keywords/restoration-ecology",
"display_name": "Restoration ecology",
"score": 0.4349832
}
],
"language": "en",
"locations": [
{
"is_oa": true,
"landing_page_url": "https://doi.org/10.1111/cobi.14203",
"pdf_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cobi.14203",
"source": {
"id": "https://openalex.org/S98137347",
"display_name": "Conservation Biology",
"issn_l": "0888-8892",
"issn": [
"0888-8892",
"1523-1739"
],
"is_oa": false,
"is_in_doaj": false,
"is_core": true,
"host_organization": "https://openalex.org/P4310320595",
"host_organization_name": "Wiley",
"host_organization_lineage": [
"https://openalex.org/P4310320595"
],
"host_organization_lineage_names": [
"Wiley"
],
"type": "journal"
},
"license": "cc-by",
"license_id": "https://openalex.org/licenses/cc-by",
"version": "publishedVersion",
"is_accepted": true,
"is_published": true
},
{
"is_oa": false,
"landing_page_url": "https://pubmed.ncbi.nlm.nih.gov/37817744",
"pdf_url": null,
"source": {
"id": "https://openalex.org/S4306525036",
"display_name": "PubMed",
"issn_l": null,
"issn": null,
"is_oa": false,
"is_in_doaj": false,
"is_core": false,
"host_organization": "https://openalex.org/I1299303238",
"host_organization_name": "National Institutes of Health",
"host_organization_lineage": [
"https://openalex.org/I1299303238"
],
"host_organization_lineage_names": [
"National Institutes of Health"
],
"type": "repository"
},
"license": null,
"license_id": null,
"version": null,
"is_accepted": false,
"is_published": false
}
],
"locations_count": 2,
"mesh": [
{
"descriptor_ui": "D003247",
"descriptor_name": "Conservation of Natural Resources",
"qualifier_ui": "Q000379",
"qualifier_name": "methods",
"is_major_topic": false
},
{
"descriptor_ui": "D017753",
"descriptor_name": "Ecosystem",
"qualifier_ui": "",
"qualifier_name": null,
"is_major_topic": false
},
{
"descriptor_ui": "D000069550",
"descriptor_name": "Machine Learning",
"qualifier_ui": "",
"qualifier_name": null,
"is_major_topic": false
},
{
"descriptor_ui": "D045483",
"descriptor_name": "Rivers",
"qualifier_ui": "",
"qualifier_name": null,
"is_major_topic": false
}
],
"ngrams_url": "https://api.openalex.org/works/W4387516284/ngrams",
"open_access": {
"is_oa": true,
"oa_status": "hybrid",
"oa_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cobi.14203",
"any_repository_has_fulltext": false
},
"primary_location": {
"is_oa": true,
"landing_page_url": "https://doi.org/10.1111/cobi.14203",
"pdf_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cobi.14203",
"source": {
"id": "https://openalex.org/S98137347",
"display_name": "Conservation Biology",
"issn_l": "0888-8892",
"issn": [
"0888-8892",
"1523-1739"
],
"is_oa": false,
"is_in_doaj": false,
"is_core": true,
"host_organization": "https://openalex.org/P4310320595",
"host_organization_name": "Wiley",
"host_organization_lineage": [
"https://openalex.org/P4310320595"
],
"host_organization_lineage_names": [
"Wiley"
],
"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/T10230",
"display_name": "Impacts of Climate Change on Marine Fisheries",
"score": 0.8705,
"subfield": {
"id": "https://openalex.org/subfields/2306",
"display_name": "Global and Planetary Change"
},
"field": {
"id": "https://openalex.org/fields/23",
"display_name": "Environmental Science"
},
"domain": {
"id": "https://openalex.org/domains/3",
"display_name": "Physical Sciences"
}
},
"publication_date": "2024-01-18",
"publication_year": 2024,
"referenced_works": [
"https://openalex.org/W1541774929",
"https://openalex.org/W1965759024",
"https://openalex.org/W1992347263",
"https://openalex.org/W2011303397",
"https://openalex.org/W2036407424",
"https://openalex.org/W2051057534",
"https://openalex.org/W2067804762",
"https://openalex.org/W2079018504",
"https://openalex.org/W2081959386",
"https://openalex.org/W2084341220",
"https://openalex.org/W2097601813",
"https://openalex.org/W2110512393",
"https://openalex.org/W2118497507",
"https://openalex.org/W2127367934",
"https://openalex.org/W2162512820",
"https://openalex.org/W2487898712",
"https://openalex.org/W2582743722",
"https://openalex.org/W2605666473",
"https://openalex.org/W2774794747",
"https://openalex.org/W2807801706",
"https://openalex.org/W2883471235",
"https://openalex.org/W2950221303",
"https://openalex.org/W2951501521",
"https://openalex.org/W2976676741",
"https://openalex.org/W3008078226",
"https://openalex.org/W3016637346",
"https://openalex.org/W3038262683",
"https://openalex.org/W3041990331",
"https://openalex.org/W3084930612",
"https://openalex.org/W3091942970",
"https://openalex.org/W3095402549",
"https://openalex.org/W3102027041",
"https://openalex.org/W3105821597",
"https://openalex.org/W3136335490",
"https://openalex.org/W3157274116",
"https://openalex.org/W3162856281",
"https://openalex.org/W4285292844",
"https://openalex.org/W4292328707",
"https://openalex.org/W4294079599",
"https://openalex.org/W4296614209",
"https://openalex.org/W4302763365",
"https://openalex.org/W4306849923",
"https://openalex.org/W4318542649",
"https://openalex.org/W4379740077"
],
"referenced_works_count": 44,
"related_works": [
"https://openalex.org/W4390569940",
"https://openalex.org/W4388422664",
"https://openalex.org/W4361193272",
"https://openalex.org/W4310278675",
"https://openalex.org/W2963326959",
"https://openalex.org/W2905433371",
"https://openalex.org/W2888392564",
"https://openalex.org/W2806259446",
"https://openalex.org/W2376344085",
"https://openalex.org/W2072145309"
],
"sustainable_development_goals": [
{
"score": 0.59,
"id": "https://metadata.un.org/sdg/15",
"display_name": "Life on land"
}
],
"title": "Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions",
"topics": [
{
"id": "https://openalex.org/T10230",
"display_name": "Impacts of Climate Change on Marine Fisheries",
"score": 0.8705,
"subfield": {
"id": "https://openalex.org/subfields/2306",
"display_name": "Global and Planetary Change"
},
"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/T10895",
"display_name": "Species Distribution Modeling and Climate Change Impacts",
"score": 0.8665,
"subfield": {
"id": "https://openalex.org/subfields/2302",
"display_name": "Ecological Modeling"
},
"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/T13398",
"display_name": "Statistical Computing and Data Analysis in R",
"score": 0.8637,
"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"
}
}
],
"type": "article",
"type_crossref": "journal-article",
"updated_date": "2024-08-11T23:54:47.752446",
"versions": []
}
}
