{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04992566,0.0008976271,0.00135728,0.003094486,0.0005406619,0.001595629,0.002367106,0.001275606,0.003535087],"category_scores_gemma":[0.1675258,0.0003288109,0.0016977,0.003163115,0.002694363,0.00212273,0.002498174,0.001765033,0.0004880253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003927295,"about_ca_system_score_gemma":0.00107964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008062756,"about_ca_topic_score_gemma":0.000666324,"domain_scores_codex":[0.9529288,0.03685515,0.002161747,0.003688806,0.003750031,0.0006153873],"domain_scores_gemma":[0.7962258,0.178966,0.008776958,0.01185265,0.002905666,0.001272889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002930266,0.0004588358,0.5459445,0.0005806925,0.003361672,0.001428472,0.0009627751,0.06285005,0.002698015,0.07632045,0.00376036,0.298704],"study_design_scores_gemma":[0.0006116026,0.003553076,0.166368,0.0001995143,0.0008837417,0.002831903,0.0006635431,0.7015063,0.003495865,0.112519,0.007168067,0.0001993971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.239152,0.001050854,0.7541595,0.0006731263,0.000162302,0.0004419133,0.001023087,0.0006530768,0.002684055],"genre_scores_gemma":[0.8289327,0.0002317821,0.167261,0.0002357867,0.000181856,0.0006432368,0.001333921,0.00010204,0.00107765],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04992566,"threshold_uncertainty_score":0.2640353,"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."}}