{"id":"W4308203212","doi":"10.1101/2022.11.02.514877","title":"Overconfidence undermines global wildlife abundance trends","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Environment Research Council; Sight Research UK; UK Research and Innovation","keywords":"Abundance (ecology); Biodiversity; Biosphere; Wildlife; Overconfidence effect; Macroecology; Geography; Ecology; Environmental resource management; Environmental science; 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":[0.01203514,0.0004110244,0.0007012141,0.001865273,0.0005700929,0.003139402,0.001142764,0.00125315,0.003158153],"category_scores_gemma":[0.05532624,0.0003011861,0.0005033924,0.00199872,0.001769799,0.004353463,0.001583686,0.001347475,0.0004345597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001380341,"about_ca_system_score_gemma":0.0008554698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01621042,"about_ca_topic_score_gemma":0.01395414,"domain_scores_codex":[0.9966717,0.001279064,0.0001896196,0.001141317,0.0005291221,0.0001892573],"domain_scores_gemma":[0.9555074,0.03014696,0.008472149,0.002484786,0.002752585,0.0006359735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005229471,0.0001011165,0.7939788,0.0002684408,0.0005141928,0.0004356972,0.001160459,0.08307806,0.001978151,0.01836414,0.008655313,0.09094265],"study_design_scores_gemma":[0.00005260794,0.0001729652,0.2898569,0.0002909821,0.0002410439,0.0004934215,0.002209245,0.593887,0.003717389,0.09827313,0.01067713,0.0001281614],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9252113,0.001021015,0.05614561,0.005765381,0.0002003918,0.00002326447,0.001734479,0.0004466547,0.009451973],"genre_scores_gemma":[0.9956219,0.00014422,0.003047867,0.0003248868,0.00009072157,0.000005963842,0.0003616995,0.00003981941,0.0003630916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01621042,"threshold_uncertainty_score":0.0636487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02166995913714612,"score_gpt":0.244105361430123,"score_spread":0.2224354022929768,"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."}}