{"id":"W4413939374","doi":"10.1093/icesjms/fsaf155","title":"The genomic consequences of fisheries collapse in a marine fish","year":2025,"lang":"en","type":"article","venue":"ICES Journal of Marine Science","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Dalhousie University","funders":"Canada First Research Excellence Fund; Ocean Frontier Institute; Fisheries and Oceans Canada; Mitacs; Alliance de recherche numérique du Canada; Dalhousie University","keywords":"Fishery; Fish <Actinopterygii>; Marine fish; Environmental science; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001057517,0.00004601843,0.00008388382,0.0001096251,0.0001142008,0.00006948477,0.0005658951,0.00002308456,0.00001993493],"category_scores_gemma":[0.000445999,0.00003411715,0.00003625429,0.0003877204,0.0009014223,0.00001284064,0.0002227514,0.00005796549,7.632029e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001437404,"about_ca_system_score_gemma":0.0004124449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003126457,"about_ca_topic_score_gemma":0.0002363596,"domain_scores_codex":[0.999235,0.0000391165,0.0003636439,0.0001073805,0.0001552806,0.00009956098],"domain_scores_gemma":[0.9990835,0.0000381681,0.0003019888,0.0001909579,0.0003597679,0.00002568745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009981745,0.00004121334,0.06575081,0.00001534466,0.00001558447,0.000001111523,0.00005711251,0.00003629428,0.9194489,0.002285419,0.001167218,0.01108119],"study_design_scores_gemma":[0.0003522791,0.0001119752,0.3365018,0.0000212593,0.000008698302,0.00002640664,0.000416027,0.00002668974,0.619645,0.00107799,0.04174544,0.00006639233],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919155,0.00009642698,0.00003641338,0.002394483,0.0003520953,0.0000548246,0.000001838945,0.000001006611,0.005147396],"genre_scores_gemma":[0.99748,0.0004122717,0.000469205,0.0001190678,0.00002247779,0.000002116871,0.00000136612,0.0000016369,0.001491898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2998039,"threshold_uncertainty_score":0.3321328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343010054759071,"score_gpt":0.2778145091457858,"score_spread":0.2643844085981951,"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."}}