{"id":"W3089767159","doi":"10.1101/2020.10.02.20205716","title":"Poor metabolic health increases COVID-19-related mortality in the UK Biobank sample","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Waist; Medicine; Confounding; Obesity; Biobank; Diabetes mellitus; Metabolic syndrome; Logistic regression; Blood pressure; Odds ratio; Demography; Internal medicine; Endocrinology; Biology; Bioinformatics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002808191,0.0003075181,0.0004963292,0.0008516897,0.0007459146,0.001346058,0.000564453,0.0005820772,0.006917131],"category_scores_gemma":[0.01358098,0.0003255593,0.0004396539,0.001941943,0.0004813562,0.0004699145,0.001702919,0.000670913,0.001144796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005089862,"about_ca_system_score_gemma":0.0004300179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03408104,"about_ca_topic_score_gemma":0.02324545,"domain_scores_codex":[0.9973743,0.001249094,0.0003030667,0.0005090691,0.0003137032,0.0002508087],"domain_scores_gemma":[0.9933518,0.001330813,0.002976964,0.001151167,0.0006271892,0.0005620715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005998994,0.00004085132,0.9869467,0.00009343045,0.000239181,0.0001568679,0.0005220031,0.00006306327,0.000314959,0.00018165,0.007699693,0.003141656],"study_design_scores_gemma":[0.00006092089,0.00005225983,0.9960711,0.00005849537,0.00007217595,0.0001903118,0.0004364476,0.0001065969,0.00008579555,0.00008725432,0.002770148,0.000008561544],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660971,0.001425844,0.0006640441,0.001384381,0.00008817561,0.00006500384,0.02744321,0.00002310765,0.002809212],"genre_scores_gemma":[0.9811029,0.0004930597,0.0007119139,0.000734149,0.00007213241,0.000125281,0.01410248,0.00001963306,0.002638416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03408104,"threshold_uncertainty_score":0.06776536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.185648364472894,"score_gpt":0.4904792464217506,"score_spread":0.3048308819488567,"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."}}