{"id":"W4386097786","doi":"10.3389/ti.2023.11589","title":"Delphi: A Democratic and Cost-Effective Method of Consensus Generation in Transplantation","year":2023,"lang":"en","type":"article","venue":"Transplant International","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Hôpital Maisonneuve-Rosemont; Ontario Brain Institute; University Health Network","funders":"Alexion Pharmaceuticals","keywords":"Medicine; Delphi method; Medical diagnosis; Delphi; Medical physics; Transplantation; Pathology; Surgery; Computer science; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3858923,0.002242952,0.002458536,0.007216542,0.007331987,0.005953521,0.005627756,0.002582665,0.02030192],"category_scores_gemma":[0.364448,0.002436314,0.001990681,0.005048982,0.005379169,0.005640517,0.02158505,0.005590678,0.003741071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005382977,"about_ca_system_score_gemma":0.01777144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001433835,"about_ca_topic_score_gemma":0.002643904,"domain_scores_codex":[0.3310935,0.6318424,0.01212743,0.006339608,0.01550046,0.003096582],"domain_scores_gemma":[0.4841452,0.4185249,0.0139561,0.03096012,0.04740532,0.005008356],"domain_codex":"methods","domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003142573,0.001722303,0.005921697,0.003475955,0.0004842856,0.001127718,0.1116628,0.006220018,0.004351473,0.0385699,0.05027283,0.7730484],"study_design_scores_gemma":[0.006955823,0.006223158,0.02156308,0.01025231,0.0007727393,0.002902013,0.1732743,0.09739433,0.01456811,0.3563372,0.3080473,0.001709736],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06520005,0.0007261359,0.8240108,0.01384484,0.001525142,0.06746649,0.0007028657,0.001126807,0.02539687],"genre_scores_gemma":[0.1297106,0.0004204612,0.7843446,0.002307,0.0004302776,0.07920364,0.0003242184,0.0002710788,0.002988091],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3858923,"threshold_uncertainty_score":0.7573041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04828953429970603,"score_gpt":0.3674036867489044,"score_spread":0.3191141524491984,"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."}}