{"id":"W4380291180","doi":"10.7759/cureus.38784","title":"Exploring ChatGPT’s Potential in Facilitating Adaptation of Clinical Guidelines: A Case Study of Diabetic Ketoacidosis Guidelines","year":2023,"lang":"en","type":"article","venue":"Cureus","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Guideline; Diabetic ketoacidosis; Data extraction; MEDLINE; Intervention (counseling); Intensive care medicine; Diabetes mellitus; Nursing; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005443958,0.000206916,0.0008670653,0.000328969,0.00004884461,0.000009366445,0.000131779,0.0001056332,0.00007278354],"category_scores_gemma":[0.04077376,0.0001956722,0.0002139768,0.0009632124,0.00006646298,0.0004081673,0.000151971,0.0002845287,0.00001988342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005221723,"about_ca_system_score_gemma":0.0002146044,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01225239,"about_ca_topic_score_gemma":0.003512573,"domain_scores_codex":[0.9922912,0.0003959408,0.005850671,0.0004817023,0.0006844971,0.0002960363],"domain_scores_gemma":[0.9946182,0.002097114,0.001011296,0.0005466193,0.001591436,0.0001353857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009863451,0.003101287,0.4411158,0.0006054491,0.0005140275,0.002775788,0.01825017,0.0204871,0.003343659,0.00001647097,0.001929921,0.506874],"study_design_scores_gemma":[0.0148543,0.003941745,0.1071589,0.0006262414,0.0008766867,0.0002322714,0.6156883,0.2553581,0.0003322102,0.0001035168,0.0004127024,0.0004149578],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956082,0.000150541,0.001178419,0.001140842,0.0007498628,0.001045922,0.00002315894,0.00008181228,0.0000213128],"genre_scores_gemma":[0.9893991,0.0003487243,0.009478956,0.0001447953,0.0003890812,0.0001236087,0.00004850143,0.00003509645,0.00003214636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5974382,"threshold_uncertainty_score":0.9943251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.816390788622117,"score_gpt":0.5836142303929812,"score_spread":0.2327765582291358,"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."}}