{"id":"W3111655147","doi":"10.1101/2020.12.09.20246736","title":"Whole genome sequencing association analysis of quantitative red blood cell phenotypes: the NHLBI TOPMed program","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Erythrocyte Function and Pathophysiology","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Institute on Aging; Kaiser Foundation Research Institute; National Human Genome Research Institute; University of Alabama; University of Alabama at Birmingham; National Heart, Lung, and Blood Institute; Northwestern University; Icahn School of Medicine at Mount Sinai; University of Minnesota; Andrea and Charles Bronfman Philanthropies; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Biology; Genetics; Genome-wide association study; Indel; Genetic association; Gene; Whole genome sequencing; Allelic heterogeneity; Population; Single-nucleotide polymorphism; Allele; Computational biology; Genome; Genotype; Medicine","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":[0.001653096,0.000367635,0.0005777464,0.001688052,0.000579099,0.0007280716,0.0005569742,0.0003235487,0.008131517],"category_scores_gemma":[0.002768693,0.0002320393,0.0005332251,0.002439444,0.0001644454,0.0001526013,0.0007004324,0.0004906176,0.0009214546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002071389,"about_ca_system_score_gemma":0.0004514333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00853281,"about_ca_topic_score_gemma":0.01279415,"domain_scores_codex":[0.9988933,0.000475938,0.00007392581,0.0003168544,0.0001640219,0.00007594035],"domain_scores_gemma":[0.9986224,0.0006460414,0.0001954175,0.0002487644,0.0001744203,0.0001128936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004299178,0.0002406475,0.6695855,0.0009072805,0.004325758,0.002256079,0.0004182348,0.007111581,0.0578775,0.003007608,0.111166,0.1388045],"study_design_scores_gemma":[0.001003774,0.0003798362,0.8708574,0.0001552603,0.002420665,0.002110447,0.000218128,0.03318203,0.01082762,0.004883182,0.07388376,0.00007788081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6352125,0.003091337,0.09802409,0.001407695,0.0001850679,0.0005818454,0.2436369,0.004794913,0.01306561],"genre_scores_gemma":[0.8292411,0.0007173065,0.05311046,0.001086327,0.0001803008,0.001027811,0.1091889,0.0006240951,0.004823607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00853281,"threshold_uncertainty_score":0.02720261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0470898686953157,"score_gpt":0.3004776068504586,"score_spread":0.2533877381551429,"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."}}