{"id":"W7133286092","doi":"","title":"NAFO subdivision 3Ps Atlantic cod stock assessment in 2023","year":2024,"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; Population; Climate change; Ecosystem; Stock assessment","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":[0.0007750294,0.0002826634,0.0001992517,0.001237946,0.0003626068,0.0004603309,0.0005507678,0.0003142875,0.002742158],"category_scores_gemma":[0.0009640211,0.0001473243,0.000578308,0.001158922,0.00007523451,0.0003019307,0.0004752603,0.0002661559,0.0011273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00212981,"about_ca_system_score_gemma":0.002419884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3607117,"about_ca_topic_score_gemma":0.4897622,"domain_scores_codex":[0.999705,0.00001676078,0.00002773561,0.00002713107,0.0001719603,0.00005134436],"domain_scores_gemma":[0.9990552,0.00002515861,0.0001325706,0.00002199613,0.0006800457,0.00008503341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004282024,0.00007821525,0.8574209,0.0001336061,0.0002310007,0.0002304772,0.0002364664,0.002392023,0.001083408,0.0008852551,0.07847688,0.05840363],"study_design_scores_gemma":[0.00004826937,0.0001101634,0.9369845,0.0001504075,0.00006917909,0.0001106784,0.0004854423,0.002416587,0.0004876877,0.0002693986,0.05884931,0.00001839536],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6888471,0.001249085,0.001891562,0.001286266,0.000274601,0.0004830431,0.2378082,0.0002139227,0.06794622],"genre_scores_gemma":[0.675938,0.001207276,0.00556262,0.001050063,0.00005960058,0.0008661225,0.2729833,0.00006353956,0.04226943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3607117,"threshold_uncertainty_score":0.7172243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01082238199844318,"score_gpt":0.2679940894786707,"score_spread":0.2571717074802275,"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."}}