{"id":"W4407423117","doi":"10.1139/cjfas-2024-0298","title":"Getting back in the black: an interactive decision-support tool to aid timely management decisions associated with Alaska black cod (sablefish) discarding","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fishery; Decision support system; Operations research; Computer science; Business; Biology; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.004076616,0.001338162,0.0004597827,0.001444143,0.0008655553,0.002799904,0.001607243,0.001922358,0.02933296],"category_scores_gemma":[0.01455728,0.0004275774,0.0007765993,0.0004731942,0.0006152663,0.002783613,0.002863498,0.00122323,0.004623622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006728634,"about_ca_system_score_gemma":0.001454596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002341,"about_ca_topic_score_gemma":0.004263762,"domain_scores_codex":[0.9988915,0.0004909277,0.0001140496,0.0001473281,0.0002735687,0.00008269325],"domain_scores_gemma":[0.9841267,0.01348466,0.0004890812,0.0004970213,0.0008062198,0.0005962879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003447883,0.002363676,0.01594185,0.002485944,0.0002867486,0.005460368,0.008388754,0.04883893,0.02604717,0.02025362,0.2317099,0.6347752],"study_design_scores_gemma":[0.001577179,0.001585985,0.01451153,0.002178765,0.0004622064,0.001706883,0.004434675,0.4197327,0.03444419,0.06683542,0.451884,0.0006464286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1811832,0.0006750541,0.565368,0.007670316,0.0007632889,0.001974908,0.01008502,0.1627469,0.06953327],"genre_scores_gemma":[0.3464587,0.000628655,0.6154036,0.00156819,0.0001868507,0.001364911,0.004794774,0.00363851,0.02595578],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02933296,"threshold_uncertainty_score":0.09812856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865614063299603,"score_gpt":0.2622627666896514,"score_spread":0.2436066260566553,"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."}}