{"id":"W1554964112","doi":"10.1002/gepi.21821","title":"Value of Mendelian Laws of Segregation in Families: Data Quality Control, Imputation, and Beyond","year":2014,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"National Institute of General Medical Sciences; National Human Genome Research Institute; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Imputation (statistics); 1000 Genomes Project; Data quality; Population stratification; Genome-wide association study; Mendelian inheritance; Genetic association; Computer science; Data mining; Missing data; Genetics; Biology; Single-nucleotide polymorphism; Machine learning; Genotype","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3333902,0.002079299,0.006881359,0.007045704,0.002742814,0.01033613,0.007288367,0.005204695,0.002458391],"category_scores_gemma":[0.5893707,0.00172325,0.002745813,0.009561534,0.02047228,0.01705451,0.007267809,0.01257142,0.0006309875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00591773,"about_ca_system_score_gemma":0.006650761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0109023,"about_ca_topic_score_gemma":0.00463784,"domain_scores_codex":[0.7351187,0.2262505,0.007451705,0.01117398,0.0187457,0.001259329],"domain_scores_gemma":[0.2644127,0.6436264,0.01587138,0.0528489,0.0212068,0.002033883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007161495,0.0001896485,0.06675205,0.002762741,0.003626479,0.0004938638,0.004708723,0.0319748,0.0003658398,0.3317713,0.02376276,0.5328757],"study_design_scores_gemma":[0.0001631561,0.0001718647,0.01004449,0.00253044,0.0004066096,0.0003381527,0.0006320704,0.06047705,0.0004236361,0.9075501,0.01705818,0.0002041567],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01520241,0.05935555,0.8356134,0.07672735,0.001887411,0.0004460088,0.001174791,0.0007784576,0.008814631],"genre_scores_gemma":[0.4204981,0.03093808,0.5223937,0.01671076,0.004253962,0.001726181,0.001234604,0.000501042,0.001743531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3333902,"threshold_uncertainty_score":0.8220485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03269438212086829,"score_gpt":0.3368635570829437,"score_spread":0.3041691749620754,"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."}}