{"id":"W2412177729","doi":"10.1002/gepi.2001.21.s1.s423","title":"Modeling Complex Disease with Demographic and Environmental Covariates and a Candidate Gene Marker","year":2001,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; University of Toronto","funders":"Mitacs","keywords":"Covariate; Logistic regression; Biology; Genetics; Proportional hazards model; Allele; Population; Regression analysis; Disease; Linkage disequilibrium; Genetic model; Genetic association; Regression; Demography; Statistics; Genotype; Single-nucleotide polymorphism; Gene; Medicine; Internal medicine; Mathematics","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":[0.0002294319,0.0001779275,0.0002274987,0.00004276691,0.0001562382,0.00001045423,0.00008285698,0.00009618101,0.00003429483],"category_scores_gemma":[0.00004810027,0.0001471712,0.00003457544,0.00003039083,0.0002087638,0.000001949602,0.0001278929,0.0000585387,0.000002221007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000307804,"about_ca_system_score_gemma":0.00001759048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001034013,"about_ca_topic_score_gemma":0.00003523273,"domain_scores_codex":[0.9988378,0.0001396125,0.0001935375,0.0004563871,0.00005043947,0.0003222756],"domain_scores_gemma":[0.9994632,0.00003719708,0.00005222885,0.0001970259,0.00001100607,0.0002393503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003528573,0.000036217,0.9669619,0.00001837632,0.0001051391,0.00003053777,0.00002947498,0.003260577,0.02665509,0.00005951821,0.0002797377,0.002210609],"study_design_scores_gemma":[0.001367516,0.0005052802,0.9171728,0.00002149423,0.0001446146,0.0004993479,0.0001607607,0.06946217,0.0001131434,0.001169708,0.008873135,0.000510008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794933,0.005242269,0.01458565,0.0003690453,0.00002575625,0.000121089,0.00007419154,0.000009049224,0.00007964145],"genre_scores_gemma":[0.9812527,0.008042139,0.009276466,0.001001712,0.00007538099,0.000008618686,0.000211142,0.00001132013,0.0001205759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06620158,"threshold_uncertainty_score":0.6001467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02129228680643129,"score_gpt":0.2327820204062412,"score_spread":0.2114897335998099,"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."}}