{"id":"W4413635998","doi":"10.2196/72371","title":"Image Generation of Common Dermatological Diagnoses by Artificial Intelligence: Evaluation Study of the Potential for Education and Training Purposes","year":2025,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Medical diagnosis; Artificial intelligence; Dermatology; Computer science; Medicine; Pathology; World Wide Web","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":[0.006367986,0.0003475664,0.0002337277,0.0008485864,0.0001484317,0.0005622435,0.0005248389,0.0004989335,0.002219259],"category_scores_gemma":[0.04034017,0.0001090444,0.0003897353,0.0003058935,0.000388042,0.0007950762,0.0004624215,0.0003605906,0.0002641255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004927212,"about_ca_system_score_gemma":0.0003133839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005855433,"about_ca_topic_score_gemma":0.0004682694,"domain_scores_codex":[0.997145,0.00172929,0.0001845695,0.0001769997,0.0006567594,0.0001073962],"domain_scores_gemma":[0.9451604,0.04651509,0.003228966,0.001248065,0.002846393,0.001001072],"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":[0.01252455,0.01148232,0.4420658,0.001127555,0.0002734358,0.0005541688,0.002835406,0.007302033,0.01020048,0.0005073732,0.001710654,0.5094162],"study_design_scores_gemma":[0.001609862,0.07420215,0.7826343,0.0004241565,0.0007040974,0.00384048,0.002894772,0.09969103,0.02716077,0.001102199,0.005589283,0.0001469823],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963697,0.0002054556,0.001413036,0.00007082784,0.00001008479,0.0002408853,0.00003953122,0.00004866836,0.001601801],"genre_scores_gemma":[0.9954231,0.0001338334,0.003888646,0.00003768861,0.00001231971,0.00009510991,0.0000677983,0.000007720941,0.0003336366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006367986,"threshold_uncertainty_score":0.03367752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05119521041674863,"score_gpt":0.3704446027748727,"score_spread":0.3192493923581241,"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."}}