{"id":"W2124082515","doi":"10.1158/1055-9965.681.13.5","title":"SNPs, Haplotypes, and Cancer: Applications in Molecular Epidemiology","year":2004,"lang":"en","type":"article","venue":"Cancer Epidemiology Biomarkers & Prevention","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Single-nucleotide polymorphism; Haplotype; Genetic association; Genetics; Tag SNP; Genetic epidemiology; Biology; SNP; Haplotype estimation; Epidemiology; Genome-wide association study; Computational biology; Bioinformatics; Medicine; Gene; Genotype; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002569353,0.000316043,0.0006966491,0.0001513705,0.0001424988,0.00000387429,0.00024516,0.0006433417,0.00003425023],"category_scores_gemma":[0.00111768,0.0003126023,0.0001908003,0.0002240694,0.0003884626,0.000009692511,0.000152158,0.0002213814,0.000009022954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001794184,"about_ca_system_score_gemma":0.0002412283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490338,"about_ca_topic_score_gemma":0.001825841,"domain_scores_codex":[0.9962091,0.001112351,0.0009510955,0.0009530599,0.00005277945,0.0007216225],"domain_scores_gemma":[0.998481,0.000313349,0.0004876976,0.000451543,0.00008319803,0.0001832056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007495957,0.00009116177,0.9632844,0.00003485924,0.0003053322,0.000001476039,0.00002777131,0.003133428,0.009620844,0.004229586,0.001412373,0.0177838],"study_design_scores_gemma":[0.00178793,0.0002799695,0.8776632,0.0001030702,0.0001343173,0.00001617046,0.00009877462,0.000206309,0.001163587,0.08556999,0.03242636,0.0005503414],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7909977,0.1081157,0.0871933,0.01186068,0.0004473731,0.001060829,0.00005797114,0.0000471796,0.0002192158],"genre_scores_gemma":[0.9395807,0.02917213,0.02471376,0.003188958,0.0003264218,0.001982787,0.0006268726,0.00005897475,0.0003493397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.148583,"threshold_uncertainty_score":0.9999326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02779129082243062,"score_gpt":0.3487699082830223,"score_spread":0.3209786174605917,"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."}}