{"id":"W2039567769","doi":"10.1016/s0377-2217(01)00271-5","title":"The development and evaluation of a fuzzy logic expert system for renal transplantation assignment: Is this a useful tool?","year":2002,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Organ Donation and Transplantation","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; St. Joseph's Hospital; McMaster University","funders":"National Research Council Canada","keywords":"United Network for Organ Sharing; Computer science; Fuzzy logic; Vagueness; Expert system; Artificial intelligence; Sorting; Operations research; Data mining; Transplantation; Mathematics; Algorithm; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007663079,0.0004703812,0.0007047894,0.001203096,0.0005925098,0.001633318,0.001265825,0.00134776,0.00402325],"category_scores_gemma":[0.02059839,0.0002725041,0.0003043654,0.0005088026,0.0003512405,0.001354455,0.0005161114,0.0006881924,0.001059059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009029541,"about_ca_system_score_gemma":0.002360407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006677718,"about_ca_topic_score_gemma":0.00704416,"domain_scores_codex":[0.9975916,0.0009823272,0.0002392988,0.0002031356,0.0008923895,0.0000913095],"domain_scores_gemma":[0.9872466,0.00518375,0.0005117739,0.0007517809,0.005811205,0.000494735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002054066,0.001400758,0.01491686,0.000615494,0.0002033031,0.0005112922,0.001126405,0.08459882,0.06795671,0.003223474,0.006165794,0.817227],"study_design_scores_gemma":[0.00072821,0.001728069,0.01359058,0.0002479723,0.0003311863,0.00078166,0.0009583773,0.9009359,0.06392962,0.003172743,0.01343441,0.0001613748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2590829,0.000352563,0.7259706,0.001242028,0.0001906295,0.001724274,0.0006523013,0.004010989,0.006773649],"genre_scores_gemma":[0.4167024,0.0001805097,0.5800763,0.0002038885,0.00003979663,0.0003751818,0.0003830146,0.00008121316,0.001957645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007663079,"threshold_uncertainty_score":0.04052675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2221657556680975,"score_gpt":0.3921952648120399,"score_spread":0.1700295091439423,"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."}}