{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004552965,0.0001542889,0.0006706143,0.00009205005,0.00003278423,0.000001375167,0.0002939113,0.0003102857,0.000006673344],"category_scores_gemma":[0.006733947,0.0001468275,0.00005548719,0.0001094098,0.0002765385,0.00000405281,0.0001811603,0.00008554001,0.000001392413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000985879,"about_ca_system_score_gemma":0.00007125462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006188355,"about_ca_topic_score_gemma":0.0004240433,"domain_scores_codex":[0.9960582,0.001850539,0.001199733,0.0005252646,0.00007021119,0.0002960539],"domain_scores_gemma":[0.9974,0.001043432,0.0006376305,0.0007244272,0.0001273703,0.00006716199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000548975,0.00006492673,0.9141931,0.00007174373,0.00009526267,1.259868e-7,0.0001125749,0.00713046,0.03794545,0.007019763,0.0009458086,0.03236591],"study_design_scores_gemma":[0.001239125,0.000366932,0.942042,0.0000105132,0.00003719917,0.000005165261,0.0001518505,0.01618375,0.0005889238,0.03776724,0.001442568,0.0001647138],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.891293,0.001356915,0.1055483,0.0009707776,0.0001120251,0.0002029371,0.0001130557,0.000004392288,0.0003986701],"genre_scores_gemma":[0.94103,0.0007509497,0.05699518,0.0007892081,0.0000631711,0.0000132375,0.00032256,0.00001174734,0.0000239185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04973705,"threshold_uncertainty_score":0.806165,"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."}}