{"id":"W4412521580","doi":"10.1016/j.jacadv.2025.102001","title":"Minimum Core Data Elements for Evaluation of Thoracic Aortic Disease","year":2025,"lang":"en","type":"review","venue":"JACC Advances","topic":"Aortic Disease and Treatment Approaches","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Marfan Foundation","keywords":"Standardization; Thoracic aortic aneurysm; Genetic data; Computer science; Clinical trial; Data set; Natural history; Verifiable secret sharing; Medicine; Disease; Data science; Set (abstract data type); Data mining; Aortic aneurysm; Medical physics; Radiology; Pathology; Internal medicine; Artificial intelligence; Aneurysm; Population","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":[0.03720343,0.001058783,0.002812189,0.006249282,0.0007343314,0.00393098,0.00391815,0.00164288,0.005311145],"category_scores_gemma":[0.07836708,0.0007485286,0.003283432,0.006034832,0.001256761,0.003584621,0.003512156,0.002595432,0.002189462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002100372,"about_ca_system_score_gemma":0.01587675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00497468,"about_ca_topic_score_gemma":0.005685187,"domain_scores_codex":[0.9792864,0.00940682,0.00566975,0.0008438075,0.004435254,0.000357972],"domain_scores_gemma":[0.9324199,0.04170673,0.005215682,0.006172176,0.01356847,0.00091714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005550819,0.0001458099,0.00624079,0.05402305,0.001032123,0.0001599822,0.0008541773,0.002769417,0.001400188,0.0668724,0.04756406,0.818383],"study_design_scores_gemma":[0.0003288357,0.0003309625,0.01569285,0.1106834,0.002002557,0.00109881,0.0009103423,0.003929538,0.004316697,0.05925771,0.8012691,0.0001790704],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.01418924,0.5475956,0.2797783,0.02953843,0.003308362,0.01214063,0.06308346,0.001924182,0.04844189],"genre_scores_gemma":[0.07475468,0.2901859,0.53641,0.006359555,0.0009105508,0.01528253,0.07279059,0.0003407856,0.002965384],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03720343,"threshold_uncertainty_score":0.1967529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.285483028005621,"score_gpt":0.5364624183561543,"score_spread":0.2509793903505333,"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."}}