{"id":"W1964735403","doi":"10.1038/nrg1318","title":"The Bayesian revolution in genetics","year":2004,"lang":"en","type":"review","venue":"Nature Reviews Genetics","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":523,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Bayesian probability; Bayesian statistics; Biology; Computational biology; Statistical genetics; Variable-order Bayesian network; Bayes' theorem; Computer science; Bayesian inference; Evolutionary biology; Data science; Machine learning; Artificial intelligence; Genetics; Genomics; Genome; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005713262,0.001235147,0.002426443,0.001995966,0.0009197819,0.002525302,0.001631747,0.004971806,0.004861061],"category_scores_gemma":[0.008557825,0.0007177407,0.0005450639,0.001987147,0.01446929,0.008115568,0.001983508,0.008551799,0.001769904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003514364,"about_ca_system_score_gemma":0.002368169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003201252,"about_ca_topic_score_gemma":0.003564787,"domain_scores_codex":[0.9978465,0.001204323,0.00008183782,0.0002198779,0.0005824009,0.00006506102],"domain_scores_gemma":[0.9937897,0.005119666,0.0001049135,0.0003497405,0.0004346954,0.0002011715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000646554,0.00004919464,0.0002125707,0.001606407,0.000118319,0.0001433087,0.0003538052,0.001695026,0.0002588113,0.5356228,0.1903926,0.2694826],"study_design_scores_gemma":[0.00003515634,0.00001818433,0.000175896,0.0006520041,0.00001610301,0.0001829541,0.00006806133,0.0005644903,0.00007842879,0.4753179,0.5228607,0.00003008173],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001745577,0.9303659,0.01642122,0.03582542,0.007132403,0.000008736748,0.00004448529,0.00007663409,0.009950641],"genre_scores_gemma":[0.01643698,0.9010246,0.01041169,0.03590393,0.02628913,0.00007681401,0.00008241106,0.0001082057,0.009666222],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005713262,"threshold_uncertainty_score":0.03021502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02420992243567337,"score_gpt":0.3168295607907124,"score_spread":0.292619638355039,"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."}}