{"id":"W4403605838","doi":"10.22541/au.172951448.86831371/v1","title":"The genomic consequences of fisheries collapse in a marine fish","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Memorial University of Newfoundland; Dalhousie University","funders":"","keywords":"Gadus; Atlantic cod; Genetic diversity; Overexploitation; Biology; Fishery; Population; Effective population size; Diversity (politics); Ecology; Geography; Fish <Actinopterygii>; Demography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002804308,0.0001125183,0.0001275096,0.00004723486,0.0000421655,0.00009188022,0.000334374,0.0001749473,0.00007687107],"category_scores_gemma":[0.00009255754,0.00008890309,0.00008429727,0.00007558976,0.0003190694,5.85639e-7,0.0007034683,0.0001550946,0.00001868002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001356809,"about_ca_system_score_gemma":0.0002597972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001418345,"about_ca_topic_score_gemma":0.001362526,"domain_scores_codex":[0.9990546,0.00005907355,0.0003786666,0.0003151491,0.0000864899,0.0001060048],"domain_scores_gemma":[0.9991953,0.00002166816,0.0001327384,0.0005227462,0.0001064016,0.00002118895],"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":[0.0001210643,0.00008664814,0.004327917,0.0004461528,0.0002338661,0.000002891808,0.0002484473,0.00009163516,0.8935384,0.01884069,0.0783401,0.003722232],"study_design_scores_gemma":[0.0002221512,0.00005895509,0.01255966,0.00006231221,0.00003514702,0.000009176981,0.0005719066,0.00007716715,0.7800999,0.008515304,0.1974628,0.0003255816],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801916,0.000654405,0.00001981499,0.004683535,0.0008522527,0.0003301936,0.00008924089,0.00001451039,0.01316441],"genre_scores_gemma":[0.9821741,0.001091698,0.0001995336,0.0001199136,0.00006186488,0.0001024907,0.0002538735,0.0000138927,0.01598263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1191227,"threshold_uncertainty_score":0.3625363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216398454997785,"score_gpt":0.2707632629505699,"score_spread":0.248599278400592,"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."}}