{"id":"W4317233185","doi":"10.1101/2023.01.14.524058","title":"If it’s there, could it be a bear?","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ursus; Geography; Population; Ecology; Demography; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008672898,0.0002138586,0.0002984164,0.0003350137,0.000922112,0.0011437,0.0003490053,0.0003954507,0.01089871],"category_scores_gemma":[0.003277813,0.0001029078,0.0002924343,0.0005405291,0.0008783754,0.0009143157,0.0003797857,0.0006516504,0.001456053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007938648,"about_ca_system_score_gemma":0.0006499256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04665167,"about_ca_topic_score_gemma":0.05938698,"domain_scores_codex":[0.999746,0.0000601913,0.000009329286,0.00007241227,0.00007512634,0.00003700905],"domain_scores_gemma":[0.9990183,0.000258252,0.0002751145,0.00007675101,0.0002428148,0.0001287871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006105247,0.0001201313,0.7704215,0.0002867289,0.000359969,0.001481352,0.001226328,0.001135696,0.002513281,0.008342338,0.1058161,0.107686],"study_design_scores_gemma":[0.00004637643,0.0001901036,0.8072697,0.0007391406,0.0003915775,0.003528735,0.01421237,0.004923181,0.004770528,0.03242282,0.1314182,0.00008733495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8577394,0.01073946,0.007020417,0.0777001,0.002842786,0.00004082384,0.003616703,0.000206763,0.04009349],"genre_scores_gemma":[0.9770663,0.002688672,0.001803226,0.00313069,0.0007516262,0.000007709841,0.000986615,0.00004732377,0.01351774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04665167,"threshold_uncertainty_score":0.09276026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02735884544048819,"score_gpt":0.2328799478017719,"score_spread":0.2055211023612837,"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."}}