{"id":"W2019936812","doi":"10.1007/s00357-013-9138-3","title":"Model Selection for the Trend Vector Model","year":2013,"lang":"en","type":"article","venue":"Journal of Classification","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Model selection; Bayesian information criterion; Statistics; Mathematics; Selection (genetic algorithm); Marginal likelihood; Likelihood function; Akaike information criterion; Likelihood-ratio test; Estimator; Curse of dimensionality; Statistic; Estimation theory; Computer science; Maximum likelihood; Artificial intelligence","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":[0.0001238125,0.0000600288,0.00006239724,0.00002078518,0.0000686791,0.00002073564,0.0001310168,0.00006951347,0.00000691207],"category_scores_gemma":[0.00004282932,0.00003976769,0.00007573298,0.00003201668,0.00002769788,0.000006378054,0.000007383857,0.00006179909,0.000001818887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001101005,"about_ca_system_score_gemma":0.00007937864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000107968,"about_ca_topic_score_gemma":0.000004542695,"domain_scores_codex":[0.9995366,0.00001485743,0.0002003416,0.00007901817,0.00008589168,0.00008332784],"domain_scores_gemma":[0.9994699,0.00001868235,0.0001901724,0.0001068916,0.0001790083,0.00003539094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009562515,0.00007367673,0.0002331736,0.000009095547,0.00006455719,4.411257e-9,0.0001173096,0.1954198,0.7510219,0.00949678,0.02597959,0.01748844],"study_design_scores_gemma":[0.0005880938,0.0004157107,0.036747,0.000006719532,0.00007588271,0.00001537328,0.0001107062,0.9240162,0.01826252,0.0153254,0.00431811,0.0001182589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2273559,0.0002092069,0.7707878,0.001022813,0.0001124499,0.0001594205,0.000003703769,0.000002228127,0.0003463715],"genre_scores_gemma":[0.9520797,0.00003589902,0.04629667,0.0001060655,0.0003101834,0.00002621794,0.000006373488,0.000009006745,0.001129915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7327594,"threshold_uncertainty_score":0.162168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04080810075278901,"score_gpt":0.2763725692418595,"score_spread":0.2355644684890705,"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."}}