{"id":"W4306811578","doi":"10.1136/openhrt-2022-002068","title":"Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement","year":2022,"lang":"en","type":"article","venue":"Open Heart","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Technische Universität München","keywords":"Cardiology; Stenosis; Internal medicine; Medicine; Aortic valve replacement; Aortic valve; Aortic valve stenosis","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004452379,0.0002742712,0.0007021965,0.0001034227,0.0001887197,0.00004365394,0.0002055704,0.00004323484,0.001656651],"category_scores_gemma":[0.00004684572,0.0001903672,0.001654932,0.0003310367,0.00008287896,0.0001307331,0.0001721967,0.0002206796,0.00002568423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001919147,"about_ca_system_score_gemma":0.0001904219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002114097,"about_ca_topic_score_gemma":0.00000228181,"domain_scores_codex":[0.9974136,0.0002864201,0.0006614114,0.0004932194,0.0007726164,0.0003727213],"domain_scores_gemma":[0.9984195,0.0001735909,0.0002244918,0.000884169,0.0001530827,0.0001451807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01264293,0.003804007,0.9591078,0.0002918029,0.006380476,0.00000318191,0.002151132,0.0004813249,0.0001672221,0.0001074808,0.0004619825,0.01440072],"study_design_scores_gemma":[0.001039267,0.002890962,0.9878672,0.0004118943,0.003882537,0.000001093244,0.001858159,0.0001388865,0.001097733,0.0003427705,0.0001519659,0.0003175622],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950618,0.0001633553,0.00002789219,0.0002330116,0.0002403856,0.002822028,0.0003376664,0.00001416669,0.001099767],"genre_scores_gemma":[0.9982902,0.00002155212,0.00008085534,0.0004617958,0.0000357083,0.0007470252,0.0001095524,0.0000523927,0.0002009494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02875943,"threshold_uncertainty_score":0.999256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02414226730184657,"score_gpt":0.2961207571568508,"score_spread":0.2719784898550043,"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."}}