{"id":"W2154874147","doi":"10.1139/f08-049","title":"An improved method for predicting the accuracy of genetic stock identification","year":2008,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":247,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Baseline (sea); Resampling; Oncorhynchus; Statistics; Chinook wind; Computer science; Mathematics; Biology; Fish <Actinopterygii>; Fishery","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":[0.006394919,0.0009061033,0.001060428,0.002324958,0.0005449314,0.001124128,0.001477912,0.001321745,0.001697936],"category_scores_gemma":[0.02641193,0.0004612155,0.0008104263,0.00144109,0.00061098,0.001602393,0.001021098,0.001600152,0.000788758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009780853,"about_ca_system_score_gemma":0.001163868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009377163,"about_ca_topic_score_gemma":0.008219083,"domain_scores_codex":[0.9964265,0.001099069,0.0002541791,0.0009783411,0.001061695,0.0001801934],"domain_scores_gemma":[0.9860632,0.007211306,0.001137862,0.002315,0.003100478,0.0001722428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005297792,0.0002328591,0.08037554,0.0001442929,0.0005139573,0.0001545941,0.0004290408,0.3462985,0.0178071,0.007198963,0.003729792,0.5425856],"study_design_scores_gemma":[0.00002494368,0.00007672212,0.00888503,0.00001530991,0.00003264131,0.0001219265,0.00001480155,0.9838173,0.003401486,0.002536083,0.001030552,0.00004321826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05066796,0.0001811488,0.9454665,0.00009386152,0.00005682396,0.00007057282,0.0003859118,0.002207002,0.0008702078],"genre_scores_gemma":[0.3950011,0.0001109747,0.6011284,0.0001138029,0.00007135389,0.0001920568,0.001130726,0.0001863414,0.002065326],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009377163,"threshold_uncertainty_score":0.03381997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02608311029038754,"score_gpt":0.2751580263312586,"score_spread":0.2490749160408711,"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."}}