{"id":"W4388194775","doi":"10.1086/728422","title":"Opening the Museum’s Vault: Historical Field Records Preserve Reliable Ecological Data","year":2023,"lang":"en","type":"article","venue":"The American Naturalist","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Field (mathematics); Ecology; Range (aeronautics); Evolutionary ecology; Environmental data; Geography; Data science; Diversity (politics); Computer science; Biology; Sociology; Engineering","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":[0.02769387,0.0003324331,0.0005266766,0.003448237,0.002267167,0.005504816,0.002184212,0.0009916301,0.004183646],"category_scores_gemma":[0.09345973,0.0006765737,0.0004522956,0.005365046,0.005825273,0.006188627,0.004473378,0.001678414,0.001166789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001427131,"about_ca_system_score_gemma":0.00321634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007460915,"about_ca_topic_score_gemma":0.01903206,"domain_scores_codex":[0.9871809,0.008351292,0.0005502818,0.001313858,0.002281183,0.0003225215],"domain_scores_gemma":[0.9128994,0.03090489,0.009736245,0.03793649,0.006024193,0.002498848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004924568,0.0002658912,0.2835643,0.0006244747,0.0003034196,0.0004990227,0.01637112,0.004572366,0.006575012,0.07532027,0.03707206,0.5743396],"study_design_scores_gemma":[0.0002305216,0.000665208,0.4772851,0.001921904,0.0003297004,0.001649637,0.01350199,0.0276845,0.009426144,0.1308617,0.3360837,0.000359889],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.546218,0.00347747,0.3653145,0.02069475,0.001323819,0.0009329531,0.008721715,0.00229822,0.0510185],"genre_scores_gemma":[0.8105298,0.0009377158,0.180138,0.001248544,0.0006353301,0.0005724909,0.002479889,0.0003594963,0.003098814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02769387,"threshold_uncertainty_score":0.146461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07771410680426155,"score_gpt":0.31008358234838,"score_spread":0.2323694755441184,"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."}}