{"id":"W2980577289","doi":"10.1126/science.aaw1620","title":"The geography of biodiversity change in marine and terrestrial assemblages","year":2019,"lang":"en","type":"article","venue":"Science","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":651,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; University of British Columbia; McGill University; Memorial University of Newfoundland","funders":"H2020 European Research Council; Deutsche Forschungsgemeinschaft; Leverhulme Trust","keywords":"Biodiversity; Species richness; Climate change; Geography; Ecology; Global change; Global biodiversity; Prioritization; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004938977,0.0001317278,0.0002392533,0.003348477,0.0003945915,0.001007693,0.0001964925,0.0002017884,0.001857947],"category_scores_gemma":[0.002268299,0.0001463966,0.0002990191,0.003595286,0.000882804,0.001060509,0.0007686412,0.0002363374,0.0002228383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004721622,"about_ca_system_score_gemma":0.0002642129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01328756,"about_ca_topic_score_gemma":0.0291942,"domain_scores_codex":[0.9995498,0.0001660809,0.00004579886,0.0001266043,0.00007716359,0.00003446753],"domain_scores_gemma":[0.9984744,0.0003349074,0.0007937368,0.0001483245,0.0001639905,0.00008448877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000252917,0.000009085011,0.9791296,0.0001297655,0.0002050116,0.00007403611,0.000599164,0.0006451447,0.002703168,0.0004653269,0.0002392921,0.01577521],"study_design_scores_gemma":[4.638001e-7,0.00000785648,0.9984739,0.000009149529,0.00001164396,0.00006154105,0.0003235758,0.0001514939,0.0000700662,0.0001974585,0.0006901453,0.000002769515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873974,0.003689509,0.001581658,0.0003107862,0.00001981561,0.00001492129,0.001691215,0.00002695355,0.005267906],"genre_scores_gemma":[0.9973186,0.001092589,0.0006179321,0.00004132597,0.000014405,0.000007393308,0.0006570329,0.000005358568,0.0002453493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01328756,"threshold_uncertainty_score":0.02642047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02162088862967867,"score_gpt":0.2411502105685742,"score_spread":0.2195293219388955,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}