{"id":"W4391534217","doi":"10.1161/circheartfailure.123.011306","title":"Enhancing the Prediction of Cardiac Allograft Vasculopathy Using Intravascular Ultrasound and Machine Learning: A Proof of Concept","year":2024,"lang":"en","type":"article","venue":"Circulation Heart Failure","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Ted Rogers Centre for Heart Research; University Health Network","funders":"","keywords":"Medicine; Lung transplantation; Intravascular ultrasound; Heart transplantation; Internal medicine; Transplantation; Cardiology; Cardiac allograft vasculopathy; Cluster (spacecraft)","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":[0.004748,0.001000277,0.001083595,0.0007757402,0.0002716462,0.001292218,0.00106802,0.001395867,0.001222307],"category_scores_gemma":[0.007892724,0.0003662785,0.001044986,0.0003531493,0.0005161296,0.001039268,0.001086171,0.001532698,0.0004868082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004378087,"about_ca_system_score_gemma":0.001477913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001911344,"about_ca_topic_score_gemma":0.001214578,"domain_scores_codex":[0.9986752,0.0006671412,0.00004260103,0.0002280139,0.000279201,0.0001078202],"domain_scores_gemma":[0.99536,0.003129747,0.0002875108,0.0002763673,0.0006669964,0.0002794608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00264763,0.005122904,0.116017,0.0002988334,0.001075823,0.0003270146,0.0001341204,0.2790197,0.01629617,0.004985792,0.006830558,0.5672445],"study_design_scores_gemma":[0.0001365768,0.0005919352,0.005377968,0.00001945807,0.00009203327,0.00008629794,0.00001692182,0.9892316,0.001880832,0.001912168,0.0006293223,0.00002492269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4677016,0.003615702,0.516665,0.004324829,0.0004064337,0.0005712968,0.0005332377,0.001703626,0.004478327],"genre_scores_gemma":[0.8054627,0.0006643356,0.1909111,0.0005374082,0.0003873136,0.0002605821,0.0004770886,0.00007281239,0.001226632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004748,"threshold_uncertainty_score":0.02511013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256638992381837,"score_gpt":0.276065176637185,"score_spread":0.2534987867133666,"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."}}