{"id":"W7133284183","doi":"","title":"Newfoundland & Labrador Comparative Fishing Analysis - Part II","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":"","keywords":"Fishing; Coast guard; Taxon; Estimation; Subdivision","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":[0.002529273,0.0004938076,0.0004448173,0.006711809,0.001551326,0.001146137,0.0008348257,0.0001991307,0.008511733],"category_scores_gemma":[0.002958623,0.0002422804,0.0007580904,0.008331566,0.0005671459,0.0004309879,0.0010243,0.0004718971,0.0009626307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01754449,"about_ca_system_score_gemma":0.009914934,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8749252,"about_ca_topic_score_gemma":0.946196,"domain_scores_codex":[0.9975498,0.0002276684,0.0001426073,0.0004148754,0.001017518,0.0006474471],"domain_scores_gemma":[0.9937288,0.0004161348,0.0009265241,0.0004021628,0.004160053,0.00036644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006101198,0.0001633384,0.7860029,0.0004062914,0.0004838254,0.0005684593,0.001240402,0.002071322,0.004187102,0.002058255,0.05690194,0.1453061],"study_design_scores_gemma":[0.000007928579,0.00007318823,0.9782469,0.00004731268,0.00002776281,0.00003997894,0.0005715596,0.0003004773,0.0004404533,0.00002692781,0.02020501,0.00001257053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8046358,0.001389392,0.004242724,0.0006297178,0.0001028378,0.001049157,0.111201,0.0002175064,0.07653196],"genre_scores_gemma":[0.7557552,0.00116074,0.01900689,0.0009009722,0.00009323666,0.001893017,0.1452157,0.000135648,0.07583846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1250748,"threshold_uncertainty_score":0.2516227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01315655872561311,"score_gpt":0.2572014765222755,"score_spread":0.2440449177966624,"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."}}