{"id":"W4410185096","doi":"10.21203/rs.3.rs-6271914/v1","title":"Enhancing Kidney Transplant Success: Simulation of Prospective Pirche-Ii Molecular Matching in Canada","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver General Hospital; McGill University; University of British Columbia","funders":"","keywords":"Matching (statistics); Kidney transplant; Kidney transplantation; Kidney; Medicine; Computer science; Internal medicine; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002757939,0.0004976924,0.0006182981,0.0004874441,0.00176094,0.001846701,0.001920623,0.001412123,0.009132815],"category_scores_gemma":[0.01158424,0.00034075,0.000727541,0.001050802,0.001401905,0.0007528497,0.001553815,0.001502117,0.0005569269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02428833,"about_ca_system_score_gemma":0.0391215,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8984665,"about_ca_topic_score_gemma":0.9188753,"domain_scores_codex":[0.9985384,0.0004772765,0.00002769669,0.0001692384,0.000133548,0.0006538305],"domain_scores_gemma":[0.9929311,0.003315434,0.0003556497,0.0003499221,0.001370147,0.001677691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003000007,0.002651875,0.08993572,0.0001368407,0.0001984375,0.0005593458,0.0007498299,0.8263212,0.0006276594,0.01983603,0.02864504,0.02733801],"study_design_scores_gemma":[0.001462456,0.001088144,0.03657199,0.00006568908,0.0001267096,0.00008774122,0.002806112,0.9355964,0.0009664997,0.008369369,0.01273467,0.000124215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707603,0.0001615834,0.003436155,0.003987642,0.00009960753,0.0003310887,0.002203509,0.0001488487,0.01887114],"genre_scores_gemma":[0.9910399,0.00009621035,0.002614086,0.0003019422,0.00001296179,0.00008839677,0.0008108959,0.00002556766,0.005009936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1015335,"threshold_uncertainty_score":0.2042628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03099663307768864,"score_gpt":0.3874965402668342,"score_spread":0.3564999071891456,"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."}}