{"id":"W4308995007","doi":"10.1038/s41586-022-05492-5","title":"Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries","year":2022,"lang":"en","type":"erratum","venue":"Nature","topic":"Cerebrovascular and genetic disorders","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill Genome Centre; Population Health Research Institute; McMaster University; Impact; McGill University; University of British Columbia; Thrombosis and Atherosclerosis Research Institute","funders":"National Human Genome Research Institute; Medical Research Council; Agence Nationale de la Recherche; Lundbeckfonden; British Heart Foundation; Wellcome Trust","keywords":"Drug discovery; Computational biology; Drug; Genetics; Biology; Medicine; Bioinformatics; Pharmacology","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":[0.0054775,0.002048384,0.001787213,0.004636403,0.00354559,0.005670656,0.003441679,0.005825227,0.1233369],"category_scores_gemma":[0.09477014,0.001309582,0.00170373,0.004243817,0.002185914,0.002390657,0.002374703,0.01267259,0.05845588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003263797,"about_ca_system_score_gemma":0.007703914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01946951,"about_ca_topic_score_gemma":0.02505372,"domain_scores_codex":[0.9933754,0.001003303,0.001165585,0.0008294228,0.003126839,0.0004993869],"domain_scores_gemma":[0.9442775,0.01739345,0.002531599,0.004620541,0.02923582,0.001941044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002000983,0.000003720954,0.00005775355,0.00005470249,0.000009115587,0.0001234459,0.00002011168,0.00002780141,0.00002651326,0.0007222,0.9948798,0.004054687],"study_design_scores_gemma":[0.00005118995,0.00001559461,0.0005645124,0.0003270084,0.00004644821,0.0006517771,0.00006639271,0.0002554175,0.0003148025,0.002378458,0.9952918,0.00003654897],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001339873,0.0005710134,0.001255804,0.05130572,0.938462,0.00002500903,0.003188668,0.0007291416,0.004328605],"genre_scores_gemma":[0.02041337,0.008680952,0.01466608,0.1298266,0.4166467,0.0003753082,0.01307458,0.005425982,0.3908904],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1233369,"threshold_uncertainty_score":0.4126032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00427690146636712,"score_gpt":0.2439020316956543,"score_spread":0.2396251302292872,"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."}}