{"id":"W4388078979","doi":"10.2196/49280","title":"Evaluation of ChatGPT Dermatology Responses to Common Patient Queries","year":2023,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dermatology; Medicine; Computer science; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005057958,0.0005926639,0.0006434513,0.00131944,0.0007374627,0.001370138,0.0007362626,0.001220259,0.005583424],"category_scores_gemma":[0.04409378,0.0001714795,0.0004423677,0.0007052657,0.0003441354,0.0008181444,0.001322039,0.0006401544,0.002540532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007530015,"about_ca_system_score_gemma":0.000981183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007204605,"about_ca_topic_score_gemma":0.008181001,"domain_scores_codex":[0.9932777,0.004365096,0.0005690525,0.0004474952,0.001108426,0.000232176],"domain_scores_gemma":[0.9398686,0.04845544,0.002000054,0.001685324,0.006123632,0.00186704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.04162794,0.01229379,0.2741104,0.007738496,0.001248293,0.005142712,0.03438348,0.008959792,0.05665133,0.001124056,0.05826415,0.4984556],"study_design_scores_gemma":[0.004250304,0.02586625,0.7172353,0.001257144,0.001817625,0.007391746,0.03313562,0.1049914,0.042967,0.001617545,0.05879623,0.0006738832],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876062,0.0003102324,0.002052026,0.0004886015,0.0001434168,0.000749142,0.003149695,0.001212221,0.004288382],"genre_scores_gemma":[0.9768747,0.0002975246,0.01070561,0.0007351202,0.0001420347,0.0005807886,0.006328928,0.0001539826,0.004181212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007204605,"threshold_uncertainty_score":0.02674937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2224496072839383,"score_gpt":0.4953655900003545,"score_spread":0.2729159827164163,"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."}}