{"id":"W3131422305","doi":"10.21203/rs.3.rs-207697/v1","title":"I’am hiQ – A Novel Accuracy Index for Imputed Genotypes","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; Public Health Ontario; Princess Margaret Cancer Centre; Lunenfeld-Tanenbaum Research Institute","funders":"National Cancer Institute; National Institutes of Health","keywords":"Imputation (statistics); Computer science; Software; Data mining; Population; Statistics; Mathematics; Medicine; Machine learning; Missing data","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02964569,0.001175476,0.001789842,0.009198621,0.0007423667,0.004505378,0.003182672,0.002505363,0.002991644],"category_scores_gemma":[0.1226156,0.0006010612,0.002100581,0.006812876,0.001749376,0.003301172,0.00266607,0.003109051,0.001293591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001561515,"about_ca_system_score_gemma":0.0008901771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001720876,"about_ca_topic_score_gemma":0.001201096,"domain_scores_codex":[0.9786638,0.009769226,0.002089725,0.003065474,0.005737029,0.0006747677],"domain_scores_gemma":[0.831772,0.1249553,0.01528466,0.01544946,0.01125393,0.001284722],"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":[0.001507515,0.0002896027,0.5100203,0.0009276925,0.003223008,0.0004018025,0.000780188,0.0801354,0.004452291,0.02105609,0.02217883,0.3550273],"study_design_scores_gemma":[0.0001952351,0.0007826579,0.2344787,0.0005915313,0.0008794894,0.002620185,0.0004230307,0.6467668,0.01263281,0.07666411,0.02343431,0.0005310155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1020078,0.00427816,0.8765563,0.001446921,0.0003811994,0.000237224,0.005223149,0.004430145,0.005439172],"genre_scores_gemma":[0.6620923,0.0005926175,0.3267041,0.0008794325,0.0005212587,0.0004751527,0.006119312,0.001175732,0.001440084],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02964569,"threshold_uncertainty_score":0.1567833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07329403320929388,"score_gpt":0.4187992644539288,"score_spread":0.3455052312446349,"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."}}