{"id":"W7133286622","doi":"","title":"Assessment of Atlantic mackerel in 2022","year":2023,"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":"","keywords":"Mackerel; Predation; Stock assessment; Baseline (sea); Stock (firearms)","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":[0.001335002,0.0004217994,0.0001892354,0.0009430876,0.0005979303,0.001056108,0.0004536996,0.0004400579,0.00373952],"category_scores_gemma":[0.001964428,0.0001615526,0.0005030361,0.0003860886,0.0002801121,0.0006404461,0.0009874066,0.000472476,0.000824446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002992853,"about_ca_system_score_gemma":0.002076071,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1429594,"about_ca_topic_score_gemma":0.3484526,"domain_scores_codex":[0.9993358,0.00005785575,0.00004032066,0.00008405785,0.0003891662,0.00009271397],"domain_scores_gemma":[0.9990786,0.00003930293,0.000136112,0.0000274892,0.0005866491,0.0001317734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003396264,0.00005732327,0.8792869,0.0001366727,0.0001705376,0.000803934,0.0007825398,0.01283695,0.00873416,0.002514819,0.008897279,0.08543927],"study_design_scores_gemma":[0.00001861413,0.0003471342,0.9205508,0.0001410064,0.00007534439,0.0002964322,0.001371992,0.02166117,0.002758478,0.001064261,0.05165267,0.00006206403],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9420837,0.0006837935,0.003383905,0.001124147,0.000112939,0.00009908113,0.003541496,0.0001312537,0.04883966],"genre_scores_gemma":[0.9809263,0.0002943102,0.002238199,0.0001876063,0.00001803985,0.00004559908,0.003462139,0.00002094624,0.0128069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8570406,"threshold_uncertainty_score":0.2842546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009823485829842347,"score_gpt":0.2611532491814265,"score_spread":0.2513297633515842,"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."}}