{"id":"W2017372317","doi":"10.1097/01.tp.0000266580.19614.f7","title":"Balancing Organ Quality, HLA-Matching, and Waiting Times: Impact of a Pediatric Priority Allocation Policy for Deceased Donor Kidneys in Quebec","year":2007,"lang":"en","type":"article","venue":"Transplantation","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Children's Hospital","funders":"","keywords":"Matching (statistics); Human leukocyte antigen; Unintended consequences; Balance (ability); Organ donation; Quality (philosophy); Waiting list; Medicine; Public economics; Operations management; Economics; Political science; Immunology; Transplantation; Law; Antigen; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004719917,0.0001516739,0.0002888019,0.0003429473,0.00005052391,0.00001497706,0.0000346215,0.00008390904,0.00001161262],"category_scores_gemma":[0.0000457282,0.0001292776,0.0001005142,0.0002994323,0.00001862025,0.0001699762,0.000001997142,0.00007726889,0.000001646955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001678243,"about_ca_system_score_gemma":0.0002668027,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02868975,"about_ca_topic_score_gemma":0.008919368,"domain_scores_codex":[0.9988272,0.00004212412,0.0005204611,0.0001998049,0.0001845248,0.0002258887],"domain_scores_gemma":[0.9992095,0.00032118,0.0001716125,0.00009098976,0.00008176669,0.0001249664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001539581,0.000199467,0.9679371,0.002449884,0.0001052478,0.00002124593,0.005199843,0.00007304226,0.01850499,0.001165914,0.000002092737,0.002801605],"study_design_scores_gemma":[0.006756092,0.0002093325,0.9861359,0.0002588208,0.000267812,0.00002586708,0.0001732639,0.0002136697,0.005574042,0.0002606132,0.000001011082,0.0001235915],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797243,0.00006342689,0.01913237,0.0001175076,0.00002732514,0.0006403383,0.00009447172,0.00003134639,0.0001689456],"genre_scores_gemma":[0.9963883,0.0003154556,0.00248536,0.00005685322,0.0001118577,0.00001162248,0.0005503093,0.00001800918,0.0000622293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01977038,"threshold_uncertainty_score":0.9777783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02085910226846146,"score_gpt":0.3660402745378993,"score_spread":0.3451811722694379,"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."}}