{"id":"W4383426621","doi":"10.7202/1101126ar","title":"The Rule of Rescue in the Era of Precision Medicine, HLA Eplet Matching, and Organ Allocation","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Bioethics","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University Health Centre; University of Alberta","funders":"Amgen Canada; Amgen","keywords":"Matching (statistics); Resource allocation; Organ donation; Allocator; Computer science; Complement (music); Intensive care medicine; Risk analysis (engineering); Medicine; Transplantation; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.1232223,0.0006281901,0.001613988,0.001804524,0.009693973,0.01770369,0.003725478,0.01863234,0.005373419],"category_scores_gemma":[0.1639438,0.0008641062,0.001298125,0.001843714,0.07540913,0.01804954,0.012252,0.04130736,0.001725256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01389478,"about_ca_system_score_gemma":0.04014016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01621123,"about_ca_topic_score_gemma":0.02016725,"domain_scores_codex":[0.9157043,0.03938859,0.007114437,0.01009603,0.02387161,0.003824933],"domain_scores_gemma":[0.8489162,0.09181211,0.01118215,0.0197662,0.01772457,0.01059876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005022138,0.00003802198,0.001158287,0.0001496699,0.00002657858,0.0002290204,0.002530725,0.0004295452,0.0002914281,0.8867008,0.05353401,0.05486164],"study_design_scores_gemma":[0.00003472968,0.00007159186,0.0009789634,0.0009872976,0.00002325292,0.0005634523,0.001373728,0.0006362313,0.0004385755,0.6825809,0.3122013,0.0001098481],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.005889039,0.01596569,0.06267396,0.8518927,0.009313451,0.00008954993,0.00009161167,0.0001723146,0.05391164],"genre_scores_gemma":[0.3134946,0.01744748,0.1054879,0.5184241,0.01712262,0.0004103342,0.0002272903,0.0003726243,0.0270131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1232223,"threshold_uncertainty_score":0.6516697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05216998741069438,"score_gpt":0.3437194853002045,"score_spread":0.2915494978895101,"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."}}