{"id":"W7133287186","doi":"","title":"Summary of 2015, 2016, and 2017 Herring Acoustic Surveys in Northwest Atlantic Fisheries Organization (NAFO) Divisions 4VWX","year":2022,"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; Nova scotia; Herring; Bay; German; Stock assessment; Commercial fishing; Stock (firearms); Survey methodology","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":[0.001781837,0.0005824202,0.0003222484,0.004334983,0.0004320438,0.0007094584,0.0004537801,0.0001722011,0.008406711],"category_scores_gemma":[0.002912224,0.0002488419,0.0003167946,0.002970086,0.000149969,0.0004671361,0.000634275,0.0002802227,0.003249069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001026513,"about_ca_system_score_gemma":0.002442563,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07327815,"about_ca_topic_score_gemma":0.1496858,"domain_scores_codex":[0.9984245,0.0001052075,0.0002339861,0.0001993375,0.0009033679,0.0001335802],"domain_scores_gemma":[0.9953975,0.0003205008,0.0007658994,0.0001453375,0.003022061,0.0003486431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005245067,0.0001289077,0.4659187,0.002993236,0.0003448216,0.0003980683,0.0009032193,0.001103664,0.004531855,0.000454091,0.3412443,0.1814547],"study_design_scores_gemma":[0.00001378204,0.0001543148,0.835133,0.0003923111,0.0000482605,0.00009820545,0.0007138197,0.000225732,0.0006208433,0.00004931228,0.1625311,0.00001928373],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2480774,0.004642561,0.003889827,0.0006292017,0.001543177,0.001065618,0.6846398,0.0006978451,0.05481465],"genre_scores_gemma":[0.2059203,0.006083618,0.004688285,0.0005670164,0.0004299269,0.001298431,0.7270176,0.0001699,0.05382487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9267219,"threshold_uncertainty_score":0.1457033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00837237101738695,"score_gpt":0.2246551656784447,"score_spread":0.2162827946610578,"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."}}