{"id":"W2946267017","doi":"10.1007/s11548-019-01998-y","title":"Dynamic, patient-specific mitral valve modelling for planning transcatheter repairs","year":2019,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Western University","funders":"Canadian Institutes of Health Research","keywords":"Workflow; Mitral valve; Mitral regurgitation; Computer science; Hemodynamics; Cardiology; Medicine; Radiology; Internal medicine; Biomedical engineering; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001639841,0.0001135921,0.0004011761,0.0002227908,0.00002876473,0.00002057905,0.0000552323,0.00007654095,0.00001730465],"category_scores_gemma":[0.00000639581,0.00009045723,0.002762992,0.00002843243,0.00003324974,0.00008737011,0.00001028566,0.0001188424,0.000001896259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005514217,"about_ca_system_score_gemma":0.00005305408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.655028e-7,"about_ca_topic_score_gemma":2.624693e-8,"domain_scores_codex":[0.999085,0.00004554449,0.000412027,0.0001515261,0.0001679275,0.0001379434],"domain_scores_gemma":[0.9989502,0.0004310757,0.0002034287,0.0000769203,0.0002436477,0.00009466928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005302601,0.0005431059,0.8814631,0.00006986661,0.01936741,0.0003961021,0.0007128806,0.01062036,0.0001737542,0.0001479209,0.003231453,0.07797147],"study_design_scores_gemma":[0.005401298,0.000937442,0.9304925,0.0006898668,0.001040539,0.00630771,0.0001232255,0.04606369,0.00003055134,0.000506834,0.008084593,0.000321782],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9427266,0.003777007,0.05071104,0.0003183826,0.002269253,0.0001225001,0.00001885524,0.0000104781,0.00004586774],"genre_scores_gemma":[0.9941871,0.0002138272,0.004911038,0.000342914,0.0002551628,0.000003334112,0.000055956,0.00001248127,0.00001824555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0776497,"threshold_uncertainty_score":0.3688739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078952487640277,"score_gpt":0.3013046427625902,"score_spread":0.2805151178861874,"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."}}