{"id":"W7133272457","doi":"","title":"NL Divs 2HJ3KLNOP4R Snow Crab Stock Assessment in 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":"Snow; Ecosystem; Biomass (ecology); Climate change; Abundance (ecology); Fish stock; Index (typography)","routes":{"ca_aff":false,"ca_fund":true,"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":[0.001089728,0.0003931936,0.0002347407,0.001706241,0.0005445658,0.0009661153,0.0006286558,0.0003052389,0.02943552],"category_scores_gemma":[0.001279835,0.0002525311,0.0003609166,0.0008780299,0.0001506177,0.0004170109,0.001272257,0.0003304147,0.01061799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003008308,"about_ca_system_score_gemma":0.003804704,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2710033,"about_ca_topic_score_gemma":0.3887812,"domain_scores_codex":[0.9994,0.00006838192,0.00004203393,0.00005524328,0.0002980352,0.0001361732],"domain_scores_gemma":[0.9982927,0.00004603517,0.0001682765,0.00006403345,0.001208373,0.0002205837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0006168382,0.0001326862,0.1931185,0.0002788944,0.0001160327,0.000550351,0.0004515257,0.004485628,0.003022753,0.002051385,0.598088,0.1970874],"study_design_scores_gemma":[0.00006788447,0.0001979121,0.3478526,0.0002991199,0.00003040038,0.0001447157,0.001153895,0.008541227,0.001803321,0.0005574907,0.6393074,0.00004401952],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.262041,0.001046434,0.01139269,0.003185737,0.0008945471,0.001500876,0.2924171,0.004035593,0.4234859],"genre_scores_gemma":[0.3534593,0.0009465906,0.01888233,0.001274946,0.00014986,0.0008831655,0.2477145,0.0006496832,0.3760396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7289966,"threshold_uncertainty_score":0.5388519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00898550646522555,"score_gpt":0.2622596870204038,"score_spread":0.2532741805551782,"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."}}