{"id":"W4415794685","doi":"10.1161/circ.152.suppl_3.4370368","title":"Abstract 4370368: AI-Predicted Osteoporosis from Preprocedural CT Scans Predicts Mortality After TAVR: A Multicenter Study","year":2025,"lang":"en","type":"article","venue":"Circulation","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Osteoporosis; Sarcopenia; Proportional hazards model; Bone density; Bone mineral; Cohort study; Cohort; Quantitative computed tomography; Gold standard (test); Multicenter study","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003076283,0.0002280561,0.0004386663,0.0001704564,0.0001156133,0.00004184394,0.00007822239,0.0001176004,0.0002547016],"category_scores_gemma":[0.000221589,0.0002022259,0.0002692945,0.000351471,0.00005024599,0.0001901303,0.00004404665,0.0003024021,0.00002893578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002363895,"about_ca_system_score_gemma":0.0002815885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002449571,"about_ca_topic_score_gemma":0.0004787678,"domain_scores_codex":[0.9979079,0.00008612606,0.0005617064,0.000583826,0.0005415484,0.0003188414],"domain_scores_gemma":[0.9986647,0.00005319703,0.000105815,0.0007471318,0.0002057627,0.0002233339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000305172,0.0004286323,0.9938803,0.0002013797,0.0005432956,0.00005797061,0.001107213,0.0001631369,0.0003382369,0.000001045893,0.0002424947,0.002731143],"study_design_scores_gemma":[0.003761199,0.00003890578,0.9918672,0.0002317825,0.0009105367,0.000003731388,0.0006912863,0.001938325,0.0001871059,0.00002705731,0.000194753,0.0001480942],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952726,0.0004937235,0.0003092381,0.0002025406,0.0006814114,0.002111791,0.0001783281,0.0002072239,0.0005431931],"genre_scores_gemma":[0.9985275,0.00001721954,0.00003392262,0.0005595438,0.0002574261,0.0001538389,0.0003883933,0.00002486159,0.00003734977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003456027,"threshold_uncertainty_score":0.8246534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0156907957210784,"score_gpt":0.3042039865622585,"score_spread":0.2885131908411801,"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."}}