{"id":"W2887351930","doi":"10.1002/gepi.22151","title":"The evidential statistical paradigm in genetics","year":2018,"lang":"en","type":"review","venue":"Genetic Epidemiology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Toronto; Cystic Fibrosis Canada; Cystic Fibrosis Foundation","keywords":"Frequentist inference; Statistical genetics; Statistical hypothesis testing; Bayesian probability; Statistical power; Approximate Bayesian computation; Sample size determination; Covariate; Statistical model; Econometrics; Statement (logic); Data science; Statistics; Computer science; Bayesian inference; Biology; Genetics; Machine learning; Artificial intelligence; Epistemology; Mathematics; Inference; Genomics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001410758,0.0004284878,0.001081307,0.0001025766,0.000156069,0.00002197708,0.0008103353,0.0008084035,0.00004702016],"category_scores_gemma":[0.0013132,0.0002922085,0.0003064224,0.0001859621,0.0005003843,0.000001053798,0.0002828521,0.0003381169,0.0001681384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005551517,"about_ca_system_score_gemma":0.0004719871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001286773,"about_ca_topic_score_gemma":0.0001011743,"domain_scores_codex":[0.994737,0.002129811,0.001356688,0.0009609816,0.000123552,0.0006919869],"domain_scores_gemma":[0.9974076,0.0006678209,0.0005310366,0.001185988,0.00004787703,0.0001597371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002284224,0.00002619992,0.000196195,0.000504808,0.00008445598,0.000003842619,0.000006372531,0.000009518004,0.00001930015,0.0006944674,0.04917312,0.9492589],"study_design_scores_gemma":[0.0001473957,0.0001646726,0.0005040475,0.0003870226,0.0001160177,0.00004983901,0.000005076947,0.00003451724,0.000008317646,0.001686019,0.9965928,0.0003042356],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003303908,0.9891761,0.008735315,0.0001571288,0.001038134,0.0005891451,0.00003517125,0.000009770005,0.0002261724],"genre_scores_gemma":[0.00004769997,0.9948316,0.002241761,0.0002416999,0.00129494,0.0003825606,0.0002952296,0.000060569,0.0006039393],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9489546,"threshold_uncertainty_score":0.999953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1073806444096307,"score_gpt":0.42659462018519,"score_spread":0.3192139757755593,"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."}}