{"id":"W4387808285","doi":"10.3389/ti.2023.12046","title":"Corrigendum: Delphi: A Democratic and Cost-Effective Method of Consensus Generation in Transplantation","year":2023,"lang":"en","type":"erratum","venue":"Transplant International","topic":"Assisted Reproductive Technology and Twin Pregnancy","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Hôpital Maisonneuve-Rosemont; University Health Network","funders":"","keywords":"Medicine; Delphi method; Democracy; Delphi; Transplantation; Intensive care medicine; Internal medicine; Law; Political science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003607156,0.000271098,0.0005526633,0.0006483948,0.00004072626,0.000006752247,0.000116321,0.0006167398,0.00005756053],"category_scores_gemma":[0.00009347581,0.0002555929,0.0001102593,0.0002306504,0.000153273,0.00004368639,0.00001190367,0.0008582167,0.000009375837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001045256,"about_ca_system_score_gemma":0.0001629751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000103998,"about_ca_topic_score_gemma":0.0003921599,"domain_scores_codex":[0.99824,0.0001315565,0.0005498251,0.0005537395,0.0003343778,0.000190494],"domain_scores_gemma":[0.9991761,0.0001598486,0.0002300584,0.0001990723,0.0001851591,0.0000497102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.01022223,0.002810987,0.06333401,0.01347131,0.009635283,0.01209977,0.01587559,0.0006234847,0.06491563,0.01880073,0.5092575,0.2789535],"study_design_scores_gemma":[0.03597759,0.003354293,0.6588649,0.03106357,0.009474929,0.02471304,0.001039513,0.1165543,0.05982661,0.01335236,0.04177421,0.004004783],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2188028,0.02304347,0.2907921,0.02508963,0.2130699,0.04778482,0.01828325,0.002562885,0.1605712],"genre_scores_gemma":[0.7574653,0.02456368,0.01795127,0.0004643517,0.002969201,0.002984866,0.03476898,0.0003423118,0.15849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5955308,"threshold_uncertainty_score":0.9999896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04780329041681209,"score_gpt":0.3353951668679864,"score_spread":0.2875918764511743,"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."}}