{"id":"W4400090125","doi":"10.1111/ddi.13900","title":"Climate, food and humans predict communities of mammals in the United States","year":2024,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Thelma Doelger Trust for Animals; National Institute of Food and Agriculture; North Carolina State University; U.S. Fish and Wildlife Service; Directorate for Biological Sciences; National Energy Technology Laboratory; Noble Research Institute","keywords":"Ecology; Abundance (ecology); Mammal; Habitat; Geography; Climate change; Macroecology; Relative species abundance; Population; Herbivore; Species distribution; Ecosystem; Species richness; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001695456,0.00005618067,0.00006144529,0.0000292301,0.0006135413,0.00003820103,0.0001054539,0.00002924775,0.002088056],"category_scores_gemma":[0.000008131709,0.0000438427,0.00002050837,0.0002512574,0.0004148271,0.0001048362,0.0005615475,0.00007986252,0.0000171447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005834489,"about_ca_system_score_gemma":0.000001550512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001376753,"about_ca_topic_score_gemma":0.001753655,"domain_scores_codex":[0.9995797,0.00004792383,0.000076213,0.00007397065,0.0001007978,0.0001214461],"domain_scores_gemma":[0.9997807,0.00008474196,0.00001465315,0.00008412641,0.000006181574,0.00002955882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001784698,0.0001642564,0.8909537,0.00008665385,0.0000214619,0.000008250181,0.01651382,0.00001818241,0.00004670293,0.08167337,0.01022602,0.0002698019],"study_design_scores_gemma":[0.0001917353,0.0000868502,0.9318357,0.00002585226,0.00003160021,0.000005285156,0.0505691,0.0003706135,0.00003541637,0.000729827,0.01603938,0.00007865219],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920347,0.0001231568,0.00007143569,0.0004612061,0.00002121163,0.00007788665,0.004104319,0.00002171313,0.003084336],"genre_scores_gemma":[0.9981388,0.0007162651,0.000002391875,0.00006997644,0.00000253899,0.000003300272,0.001047555,0.000001195237,0.00001802038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08094355,"threshold_uncertainty_score":0.9988242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04127589268318986,"score_gpt":0.2387916953837479,"score_spread":0.197515802700558,"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."}}