{"id":"W4247262967","doi":"10.1002/9781118584538.ieba0006","title":"Quantitative genetics","year":2018,"lang":"en","type":"other","venue":"The International Encyclopedia of Biological Anthropology","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Quantitative genetics; Quantitative trait locus; Pleiotropy; Biology; Trait; Evolutionary biology; Genetic architecture; Selection (genetic algorithm); Inheritance (genetic algorithm); Multivariate statistics; Extant taxon; Genetic variation; Genetics; Phenotype; Gene; Statistics; Mathematics; Computer science; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002753229,0.0002414239,0.0004450108,0.0001227658,0.00005802114,0.000007512481,0.000927474,0.0004666203,0.05380547],"category_scores_gemma":[0.0009322235,0.0001259197,0.0001532829,0.0001207298,0.001851993,0.000009979542,0.0003318684,0.0001992743,0.0004761796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002168178,"about_ca_system_score_gemma":0.00003475523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001491456,"about_ca_topic_score_gemma":0.00006783406,"domain_scores_codex":[0.9986183,0.0001642948,0.0004459017,0.0003312014,0.0002259157,0.0002144085],"domain_scores_gemma":[0.9980247,0.0009455598,0.0005397264,0.0003367332,0.0001125428,0.00004071692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002732548,0.000159962,0.0003268298,0.000008717053,0.0001698126,0.000006284391,0.00001938763,1.168817e-7,0.00006171949,0.26784,0.7305459,0.0008339798],"study_design_scores_gemma":[0.0001674217,0.0004462138,0.000190869,0.00003386338,0.00003605912,0.0000148793,0.0001188154,0.00003538941,0.00008595047,0.08846168,0.9102315,0.0001772937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001316482,0.0005596312,0.007351764,0.001801972,0.001970085,0.0002660467,0.0002100004,0.0001075592,0.9864165],"genre_scores_gemma":[0.007343855,0.01524812,0.09351271,0.000675177,0.002811627,0.0000760889,0.0001911678,0.0002646855,0.8798766],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1796857,"threshold_uncertainty_score":0.9470595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0710201853596476,"score_gpt":0.366024785266678,"score_spread":0.2950045999070304,"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."}}