{"id":"W2289905628","doi":"10.1139/cjfas-2015-0332","title":"Identifying blue whiting (<i>Micromesistius poutassou</i>) stock structure in the Northeast Atlantic by otolith shape analysis","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia; European Commission; Institut Français de Recherche pour l'Exploitation de la Mer","keywords":"Otolith; Fishery; Geography; Oceanography; Stock (firearms); Fish stock; Environmental science; Biology; Fish <Actinopterygii>; Geology; Archaeology","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":[0.0003182252,0.0001534677,0.0001124944,0.001044419,0.0002159776,0.0002418297,0.000143139,0.0001146358,0.0005438863],"category_scores_gemma":[0.0006026734,0.0001030108,0.0001707394,0.0005921354,0.0002016946,0.0002652538,0.0003141392,0.00009987687,0.0001498963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003172534,"about_ca_system_score_gemma":0.0002268114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04135979,"about_ca_topic_score_gemma":0.1673482,"domain_scores_codex":[0.9998777,0.00001816372,0.00001351041,0.00003424998,0.00003211219,0.00002429985],"domain_scores_gemma":[0.9996732,0.00003970274,0.0001614868,0.00002206436,0.00005974617,0.00004387059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001577241,0.000003452702,0.9933274,0.000002405199,0.000005895388,0.00002147006,0.00009869082,0.00003793414,0.003112679,0.000007997048,0.00001159555,0.003354857],"study_design_scores_gemma":[5.740224e-7,0.00001328058,0.9994569,0.000001133811,0.00000215308,0.00002527982,0.0001264013,0.0001482262,0.0001884128,0.000005016101,0.00003170948,9.575359e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996951,0.00001503479,0.000114177,0.000004195159,4.528789e-7,0.00000171418,0.00004468082,0.000001068723,0.0001235626],"genre_scores_gemma":[0.9991922,0.00002467002,0.0004981611,0.000005071896,8.334528e-7,0.000003017517,0.0001358697,7.581924e-7,0.0001394851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04135979,"threshold_uncertainty_score":0.08223808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01680443702371474,"score_gpt":0.2307335208068416,"score_spread":0.2139290837831268,"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."}}