{"id":"W3112768575","doi":"10.1101/2020.12.03.20242776","title":"Genome-wide analysis of 944,133 individuals provides insights into the etiology of hemorrhoidal disease","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Anorectal Disease Treatments and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Novo Nordisk Fonden; Novo Nordisk; Austrian Science Fund; European Regional Development Fund; Horizon 2020 Framework Programme; Deutsche Forschungsgemeinschaft; Vetenskapsrådet; Eesti Teadusagentuur; Tartu Ülikool; Deutsches Zentrum für Herz-Kreislaufforschung","keywords":"Etiology; Genome-wide association study; Heritability; Biology; Disease; Transcriptome; Extracellular matrix; Population; Genetic architecture; Genetics; Genetic association; Genetic predisposition; Bioinformatics; Gene; Pathology; Quantitative trait locus; Medicine; Gene expression; Single-nucleotide polymorphism; 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":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001577231,0.00054848,0.0007834227,0.0009371798,0.0004389652,0.0009818223,0.0003462348,0.0005213276,0.004155524],"category_scores_gemma":[0.002532159,0.0003002523,0.001609849,0.002554652,0.00022618,0.0002593461,0.000520824,0.0006253232,0.0004321981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002000337,"about_ca_system_score_gemma":0.0002755052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002469544,"about_ca_topic_score_gemma":0.002704842,"domain_scores_codex":[0.9990327,0.0003248313,0.00007569489,0.0003487808,0.0001348557,0.00008306737],"domain_scores_gemma":[0.9988272,0.0005176783,0.0002631325,0.0002335985,0.00008070816,0.00007766701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00259564,0.00008638555,0.9338637,0.000509214,0.01831069,0.0005335336,0.0001415466,0.001168815,0.0100654,0.000384218,0.005057997,0.02728307],"study_design_scores_gemma":[0.000223332,0.0001864533,0.9791723,0.00008513379,0.009169821,0.0006520873,0.0001332809,0.001011367,0.001696871,0.0009528101,0.00669534,0.00002123833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551407,0.01330357,0.004652356,0.0009605349,0.0001036979,0.0000275797,0.0233514,0.0001511362,0.0023091],"genre_scores_gemma":[0.9882684,0.001913782,0.001360961,0.0001758659,0.00006431446,0.00002702579,0.007398657,0.00002886262,0.0007621549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004155524,"threshold_uncertainty_score":0.01390159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02340216755696535,"score_gpt":0.2888110843611748,"score_spread":0.2654089168042094,"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."}}