{"id":"W7133279369","doi":"","title":"NAFO Subdivision 3Ps Atlantic Cod Stock Assessment to 2024","year":2025,"lang":"en","type":"other","venue":"Federal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fisheries and Oceans Canada","keywords":"Stock (firearms); Fishing; Ecosystem; Population; Climate change; Stock assessment; Fish stock","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0009257302,0.0003338,0.0001796059,0.001325662,0.0003677064,0.0005642852,0.0007340068,0.000334161,0.005406064],"category_scores_gemma":[0.001178159,0.0001611776,0.00052599,0.0009082058,0.00007799819,0.0003447659,0.0005180091,0.0002990881,0.001798974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002229125,"about_ca_system_score_gemma":0.003930946,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3775094,"about_ca_topic_score_gemma":0.436421,"domain_scores_codex":[0.9996296,0.0000226569,0.00002464692,0.00002599438,0.0002327826,0.0000643469],"domain_scores_gemma":[0.9989606,0.00002316939,0.00009020664,0.00002178777,0.0008279975,0.00007624459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007478805,0.0001767103,0.4198697,0.0003757441,0.000355896,0.0003922588,0.0002438289,0.007319992,0.002075457,0.003359859,0.3819961,0.1830866],"study_design_scores_gemma":[0.000139017,0.0002466351,0.6013495,0.000441683,0.0001567019,0.0001392439,0.0006153943,0.007196167,0.001546552,0.001057034,0.3870691,0.00004285805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3733425,0.00167464,0.004385266,0.003565002,0.0008181056,0.001017569,0.39522,0.0005649137,0.219412],"genre_scores_gemma":[0.45241,0.001840153,0.01179539,0.001843687,0.0001052093,0.001296637,0.3947642,0.0001131142,0.1358316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6224906,"threshold_uncertainty_score":0.7506241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008743587265349984,"score_gpt":0.2660553452434933,"score_spread":0.2573117579781434,"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."}}