{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009481042,0.00060144,0.002283163,0.001243386,0.002257115,0.00605314,0.001946801,0.02838691,0.01124061],"category_scores_gemma":[0.0587266,0.0006577916,0.001300629,0.001731442,0.002823285,0.008189281,0.001644984,0.02840248,0.007644257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005695145,"about_ca_system_score_gemma":0.006715921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008251537,"about_ca_topic_score_gemma":0.01646858,"domain_scores_codex":[0.9898571,0.00470911,0.001833909,0.0007283759,0.002185847,0.0006856045],"domain_scores_gemma":[0.9225655,0.05058199,0.006210124,0.001688324,0.01070111,0.008252867],"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":[0.0001179251,0.0000375472,0.002115738,0.0001831016,0.00003359434,0.001110624,0.00009527028,0.0000954945,0.0001068192,0.002380102,0.9686024,0.02512146],"study_design_scores_gemma":[0.0002916068,0.000116851,0.005215288,0.002855888,0.0001076336,0.003192678,0.001524639,0.001299373,0.0001932837,0.02889658,0.9561198,0.0001862033],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001802473,0.001607309,0.0000618502,0.9935983,0.003414712,0.000003434849,0.0001861961,0.0000136306,0.0009342826],"genre_scores_gemma":[0.005276283,0.004912114,0.0005737264,0.9221043,0.06505456,0.00003287675,0.0003021428,0.00003124915,0.001712701],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02838691,"threshold_uncertainty_score":0.05014116,"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."}}