{"id":"W4389438049","doi":"10.1097/tp.0000000000004876","title":"Clinical Deployment of Machine Learning Tools in Transplant Medicine: What Does the Future Hold?","year":2023,"lang":"en","type":"review","venue":"Transplantation","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network","funders":"","keywords":"Software deployment; Prioritization; Medicine; Transplantation; Organ transplantation; Matching (statistics); Intensive care medicine; Clinical decision making; Computer science; Medical physics; Surgery; Management science; Pathology; Engineering; Software engineering","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":[0.0110628,0.0008879644,0.001826361,0.00244215,0.0004318519,0.003564388,0.002084827,0.003360722,0.004855371],"category_scores_gemma":[0.01795649,0.0005809795,0.001716638,0.002512139,0.001390571,0.006056021,0.001706819,0.004496173,0.002346658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001590916,"about_ca_system_score_gemma":0.00572613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002839288,"about_ca_topic_score_gemma":0.004372575,"domain_scores_codex":[0.997372,0.001362344,0.0003007672,0.0002345811,0.0005637169,0.0001665051],"domain_scores_gemma":[0.9795296,0.01491445,0.0009635862,0.0004152464,0.003652155,0.0005249492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007374968,0.00007595285,0.0005106219,0.02243956,0.0001656846,0.0001239852,0.0001614455,0.0007041463,0.0002734192,0.0125158,0.02249043,0.9404651],"study_design_scores_gemma":[0.00006763506,0.0003093552,0.001999104,0.07458961,0.0004109316,0.0009409956,0.000553836,0.0008828791,0.0004466946,0.01505523,0.9046707,0.0000729817],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001331686,0.9918835,0.000537509,0.006201275,0.0003651605,0.00001380391,0.00002111016,0.00001190498,0.0008325432],"genre_scores_gemma":[0.001722298,0.9944726,0.001351685,0.001853988,0.0003625936,0.00002798321,0.00003190801,0.000006660961,0.0001702968],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.0110628,"threshold_uncertainty_score":0.05850637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3457471927362444,"score_gpt":0.5183723510384571,"score_spread":0.1726251583022127,"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."}}