{"id":"W4403054127","doi":"10.1139/cjfas-2023-0159","title":"Stock identification of sympatric Atlantic cod populations in the Gulf of Maine and mixed stock fishery analysis using otolith-based techniques","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Otolith; Fishery; Sympatric speciation; Stock (firearms); Atlantic cod; Cod fisheries; Stock assessment; Geography; Oceanography; Biology; Fishing; Ecology; Gadus; Fish <Actinopterygii>; Geology","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":[0.001062444,0.0002273911,0.000157499,0.001937958,0.0002924189,0.0004099315,0.0002360674,0.0001618478,0.0004723821],"category_scores_gemma":[0.001522886,0.0001130434,0.0001849085,0.0004510113,0.0002134544,0.0005155452,0.0004714511,0.00009168798,0.0001258789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006723275,"about_ca_system_score_gemma":0.0002868552,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.026355,"about_ca_topic_score_gemma":0.1401387,"domain_scores_codex":[0.9998056,0.00002542774,0.00002590133,0.00005461527,0.00006009102,0.00002845909],"domain_scores_gemma":[0.9992523,0.0001177563,0.0002055089,0.00005176804,0.0002891947,0.00008349844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003106207,0.000006391842,0.993056,0.000003858902,0.00002005204,0.0000220962,0.0001571317,0.00006099257,0.002111577,0.00001655227,0.00002081602,0.004493463],"study_design_scores_gemma":[0.000001527002,0.00003437803,0.9984548,0.000004147653,0.000008372237,0.0000254683,0.0002163148,0.0006760439,0.000516682,0.0000138544,0.00004654098,0.00000196129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996686,0.00005447099,0.0001055687,0.000005189821,9.264273e-7,0.000002895885,0.00004544513,0.000001535106,0.0001153318],"genre_scores_gemma":[0.9990075,0.00005819289,0.0005260065,0.000008908038,0.000001357598,0.000005501367,0.0002032682,0.000001237372,0.0001879869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.973645,"threshold_uncertainty_score":0.05240321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04557204193804112,"score_gpt":0.2883953975144861,"score_spread":0.2428233555764449,"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."}}