{"id":"W3015831956","doi":"10.1111/biom.13270","title":"Retrospective versus prospective score tests for genetic association with case‐control data","year":2020,"lang":"en","type":"article","venue":"Biometrics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Logistic regression; Genetic association; Statistics; Odds ratio; Score test; Contrast (vision); Random effects model; Association (psychology); Prospective cohort study; Computer science; Odds; Likelihood-ratio test; Econometrics; Medicine; Artificial intelligence; Mathematics; Biology; Internal medicine; Genetics; Psychology; Genotype; Meta-analysis; Single-nucleotide polymorphism","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":[],"consensus_categories":[],"category_scores_codex":[0.0003909792,0.0001655973,0.0002484525,0.0001130822,0.0001356269,0.00003120289,0.0002728085,0.0002371169,0.000007187513],"category_scores_gemma":[0.0057589,0.0001494324,0.00005881623,0.0009981868,0.00003658713,0.000005986813,0.0001191174,0.00008999022,0.000008797213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001410846,"about_ca_system_score_gemma":0.0001221942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002287566,"about_ca_topic_score_gemma":0.00006853914,"domain_scores_codex":[0.9985651,0.00007012895,0.0002317842,0.0006286547,0.0001731926,0.0003311227],"domain_scores_gemma":[0.9986171,0.0001672237,0.0002715331,0.0004280123,0.0003917227,0.0001244332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004091574,0.00006448301,0.9777907,0.0000167477,0.0005011034,0.00001995021,0.00004302783,0.0001014854,0.004482816,0.00004007893,0.01404069,0.00248974],"study_design_scores_gemma":[0.006705389,0.00419046,0.9665388,0.000004867228,0.0003756545,0.00005089211,0.0001394661,0.003572001,0.0009391263,0.00007911554,0.01691563,0.000488623],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9028175,0.001300508,0.08970334,0.001705435,0.0004090257,0.001324579,0.002266016,0.00004716378,0.0004264066],"genre_scores_gemma":[0.9808211,0.00007359953,0.01756755,0.0003697422,0.0006035166,0.00006132818,0.0003665121,0.00002897244,0.0001076491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07800362,"threshold_uncertainty_score":0.6894357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05680102457148995,"score_gpt":0.3061792503202541,"score_spread":0.2493782257487641,"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."}}