{"id":"W2811218732","doi":"10.1002/wsb.891","title":"From climate to caribou: How manufactured uncertainty is affecting wildlife management","year":2018,"lang":"en","type":"article","venue":"Wildlife Society Bulletin","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Toronto; Lakehead University; Northern Ontario Academic Medicine Association","funders":"Wildlife Conservation Society","keywords":"Woodland caribou; Boreal; Wildlife; Threatened species; Climate change; Geography; Taiga; Wildlife management; Habitat; Ecology; Environmental resource management; Environmental science; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001206003,0.00042034,0.0006043559,0.00004592327,0.007602313,0.0000440542,0.0004222459,0.0004426433,0.004050134],"category_scores_gemma":[0.00009133152,0.0003827503,0.0003494683,0.0002237887,0.0001598753,0.00003510343,0.001161575,0.0007089591,0.005259225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008240589,"about_ca_system_score_gemma":0.0001013324,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007329896,"about_ca_topic_score_gemma":0.003239863,"domain_scores_codex":[0.9954786,0.0003237129,0.00052321,0.00085228,0.0003979644,0.002424283],"domain_scores_gemma":[0.9980882,0.000369443,0.0003046482,0.0006604082,0.0002689124,0.0003084229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006906941,0.00005323166,0.008302768,0.0001429819,0.0003338185,0.000007075433,0.124497,0.00001304922,0.00001144533,0.00007129496,0.8660061,0.0004922129],"study_design_scores_gemma":[0.0009915658,0.0001647812,0.007912112,0.0001321514,0.0000907355,6.450839e-7,0.1538726,0.00004360804,0.00001274171,0.00006393804,0.8363513,0.0003638175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6206561,0.0001335871,0.0009790607,0.3479556,0.005247266,0.004010416,0.0006021392,0.0005581299,0.01985774],"genre_scores_gemma":[0.5066571,0.0006215208,0.01112096,0.4649987,0.006827024,0.0006366657,0.0002097804,0.0001576831,0.008770603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1170431,"threshold_uncertainty_score":0.9998624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02217540669100682,"score_gpt":0.325294681450243,"score_spread":0.3031192747592362,"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."}}