{"id":"W4416409124","doi":"10.1016/j.cjca.2025.11.012","title":"Novel Artificial Intelligence Applications in Heart Transplantation","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Abbott Pharmaceuticals","keywords":"Heart transplantation; Transformative learning; Matching (statistics); MEDLINE; Artificial heart; Transplantation; Applications of artificial intelligence; Organ transplantation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001247099,0.000407314,0.0003207089,0.0006703965,0.0003577152,0.00219104,0.0007654133,0.00071416,0.004256203],"category_scores_gemma":[0.00392178,0.0001387909,0.000353347,0.0008177259,0.0004401644,0.0008775771,0.0008069029,0.0008465746,0.0006427703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003624606,"about_ca_system_score_gemma":0.0005355061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001175004,"about_ca_topic_score_gemma":0.001892668,"domain_scores_codex":[0.9994946,0.0002343613,0.00003229952,0.00005454972,0.0001466842,0.00003755718],"domain_scores_gemma":[0.9986268,0.0008496239,0.00008631232,0.0001163708,0.0002453565,0.00007552817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003818674,0.0005125901,0.01394832,0.0007421648,0.0001812407,0.0009346216,0.0005952726,0.03772932,0.006704025,0.05918039,0.02052031,0.85857],"study_design_scores_gemma":[0.000137061,0.0006758048,0.01385199,0.0005951871,0.0002307648,0.001970219,0.001013022,0.6842979,0.01084656,0.18761,0.09868246,0.0000890233],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.2311512,0.03057814,0.5542666,0.02145261,0.002862351,0.0004793423,0.0006477128,0.001826655,0.1567354],"genre_scores_gemma":[0.7823011,0.009938877,0.1929606,0.001141613,0.0008543138,0.0001345832,0.0003450268,0.00007403357,0.01224971],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004256203,"threshold_uncertainty_score":0.01423836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04266184745882624,"score_gpt":0.3421838802249001,"score_spread":0.2995220327660739,"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."}}