{"id":"W4415022001","doi":"10.1093/ehjdh/ztaf115","title":"Unsupervised machine learning analysis to enhance risk stratification in patients with asymptomatic aortic stenosis","year":2025,"lang":"en","type":"article","venue":"European Heart Journal - Digital Health","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre hospitalier de l'Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Agence Nationale de la Recherche","keywords":"Risk stratification; Asymptomatic; Risk assessment; Stenosis; Unsupervised learning; Medical imaging","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003548049,0.0001785897,0.0004704433,0.0005085318,0.0002074952,0.0001741726,0.00006474306,0.00001544371,0.00002589923],"category_scores_gemma":[0.0001493475,0.0001376937,0.000386784,0.001192639,0.00001731606,0.0001968638,0.00002925015,0.0003143326,0.00007845078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002756795,"about_ca_system_score_gemma":0.000177178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006462774,"about_ca_topic_score_gemma":0.000008302566,"domain_scores_codex":[0.9981504,0.0003003187,0.0005675088,0.000290229,0.0003668468,0.0003247077],"domain_scores_gemma":[0.9989125,0.00006582654,0.000179143,0.0002560765,0.0001473609,0.0004390858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002790738,0.0005449103,0.9644843,0.00005303756,0.0008405622,0.0000118426,0.0001732549,0.0004106658,0.000001074639,0.000001926105,0.00008052927,0.03311878],"study_design_scores_gemma":[0.001300984,0.0009949994,0.9962831,0.0003080455,0.0005315323,0.000002105179,0.0000887968,0.0002542737,0.000003073017,0.000007974018,0.0001241175,0.0001010377],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967718,0.0002735689,0.000431098,0.000595635,0.00004645187,0.0004838783,0.00005244343,0.00003627345,0.001308927],"genre_scores_gemma":[0.9986311,0.00006093414,0.0002220311,0.000577528,0.00002860449,0.000004752504,0.0001557015,0.0000259661,0.0002933404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03301774,"threshold_uncertainty_score":0.5614988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01063695023781039,"score_gpt":0.3348840971275104,"score_spread":0.3242471468897,"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."}}