{"id":"W4394611114","doi":"10.3354/esr01333","title":"Discriminating Canadian Arctic beluga management stocks using dentine oxygen and carbon isotopes","year":2024,"lang":"en","type":"article","venue":"Endangered Species Research","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Fisheries and Oceans Canada","funders":"","keywords":"Beluga; Beluga Whale; Arctic; Environmental science; Carbon fibers; Fishery; Oceanography; Biology; Geology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008422956,0.0004487423,0.0003219594,0.001475953,0.001727533,0.0009763169,0.0004347896,0.0002962332,0.0005992271],"category_scores_gemma":[0.001604954,0.0002768006,0.0002818499,0.001064467,0.0005835114,0.0003709209,0.0004270591,0.0002758016,0.0001617425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003852987,"about_ca_system_score_gemma":0.002508759,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8867465,"about_ca_topic_score_gemma":0.9709496,"domain_scores_codex":[0.9995638,0.00004710508,0.0000273606,0.0001245828,0.0001041222,0.0001330252],"domain_scores_gemma":[0.9990867,0.0001001997,0.0001460285,0.00004710654,0.0004206099,0.0001992973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001293875,0.00003484024,0.9793366,0.00001372082,0.00007288868,0.00008361304,0.001357809,0.0005077836,0.005771542,0.00007205172,0.0003218595,0.01229801],"study_design_scores_gemma":[0.00000400018,0.00003139342,0.9965019,0.000007912558,0.00003078058,0.00005700803,0.001237846,0.001292239,0.0002990687,0.00003699077,0.0004885062,0.00001247627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988515,0.00007195801,0.0002815707,0.00002232557,0.000003398548,0.000008981573,0.0001877413,0.000006164649,0.0005663335],"genre_scores_gemma":[0.9978611,0.000109507,0.001109715,0.00003384228,0.000002785993,0.00001072015,0.000472445,0.00000453522,0.0003953601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1132535,"threshold_uncertainty_score":0.2278408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0809788546047033,"score_gpt":0.3301820110755437,"score_spread":0.2492031564708404,"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."}}