{"id":"W2100901986","doi":"10.1017/s0016672302006055","title":"Marker-assisted estimation of quantitative genetic parameters in rainbow trout, <i>Oncorhynchus mykiss</i>","year":2003,"lang":"en","type":"article","venue":"Genetics Research","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Guelph","funders":"","keywords":"Pairwise comparison; Rainbow trout; Statistics; Markov chain Monte Carlo; Mathematics; Regression; Contrast (vision); Covariance; Estimator; Biology; Computer science; Bayesian probability; Artificial intelligence; Fish <Actinopterygii>; Fishery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001034577,0.0002078409,0.0002548653,0.0002360201,0.0000891493,0.00002857922,0.0003676674,0.0002344429,0.00003494788],"category_scores_gemma":[0.0006333842,0.000216317,0.00009209973,0.0005273654,0.0004140757,0.00000338415,0.0001058024,0.0002700735,0.00001826262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003598808,"about_ca_system_score_gemma":0.0003248837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004735453,"about_ca_topic_score_gemma":0.00007567379,"domain_scores_codex":[0.997046,0.0008063083,0.0005039939,0.000534079,0.0005190904,0.0005905451],"domain_scores_gemma":[0.9986895,0.0001693337,0.0001053695,0.0006210283,0.0002665944,0.0001481431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001163978,0.001474509,0.04491867,0.0004020913,0.0003320776,0.00001873394,0.002158897,0.2207491,0.6300123,0.01264089,0.00378522,0.08234359],"study_design_scores_gemma":[0.002842826,0.003395913,0.5222821,0.00009608809,0.00003660802,0.0000430865,0.001267589,0.002465818,0.4483111,0.01412143,0.004458018,0.0006793892],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783893,0.00260585,0.01385178,0.00004700235,0.00008819749,0.0005505956,0.00002294303,0.000006697984,0.004437607],"genre_scores_gemma":[0.7890855,0.0002088726,0.2101327,0.00003029846,0.00002102522,0.00005694119,0.0000318875,0.00003045311,0.000402321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4773634,"threshold_uncertainty_score":0.8821152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06101230383000193,"score_gpt":0.3584037045258384,"score_spread":0.2973914006958364,"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."}}