{"id":"W3044442320","doi":"10.1016/j.carrev.2020.06.038","title":"MitraClip Real-World Data: What Is Missing and Looking Into the Future","year":2020,"lang":"en","type":"letter","venue":"Cardiovascular revascularization medicine","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Medicine; MitraClip; Real world data; Missing data; Data science; Internal medicine; Statistics; Mitral valve","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009392002,0.0008629214,0.002426692,0.0003313094,0.0004710863,0.000302655,0.000528755,0.0004712069,0.00009388448],"category_scores_gemma":[0.0002414998,0.0005729203,0.00343802,0.001095688,0.0005954191,0.0004609176,0.0004311141,0.001773927,0.00003957974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002184001,"about_ca_system_score_gemma":0.0002542316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004918989,"about_ca_topic_score_gemma":0.000006918647,"domain_scores_codex":[0.993946,0.0005644049,0.0007856803,0.001818247,0.002340773,0.0005448668],"domain_scores_gemma":[0.994294,0.0001706879,0.0003351492,0.004412099,0.0003965773,0.0003914479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006814524,0.00003400215,0.005616893,0.002757894,0.04076903,0.002437901,0.001202808,0.000007817427,0.000009310403,0.00002411649,0.7100568,0.2370152],"study_design_scores_gemma":[0.002723261,0.00008583161,0.006442608,0.002077994,0.03955678,0.0001636509,0.0005915815,0.0001832159,0.000007040918,0.0001219835,0.9475542,0.0004918648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001922943,0.3210394,0.00149029,0.6735288,0.001480237,0.001656458,0.00004674877,0.0001520943,0.000413624],"genre_scores_gemma":[0.001561291,0.2118977,0.0004732356,0.7344697,0.03631812,0.0000852999,0.01419278,0.0003136926,0.0006881848],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2374973,"threshold_uncertainty_score":0.9996722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02585780320550989,"score_gpt":0.3202400801078791,"score_spread":0.2943822769023692,"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."}}