{"id":"W4400174108","doi":"10.2196/55204","title":"Readability of Information Generated by ChatGPT for Hidradenitis Suppurativa","year":2024,"lang":"en","type":"letter","venue":"JMIR Dermatology","topic":"Hidradenitis Suppurativa and Treatments","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hidradenitis suppurativa; Readability; Medicine; Computer science; Information retrieval; Dermatology; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.000004922516,0.0004775469,0.001162596,0.0003703739,0.00007062767,0.00004091973,0.0001610716,0.001487827,0.0003012995],"category_scores_gemma":[0.00008196328,0.0003989638,0.000317418,0.0002570534,0.0002296763,0.000297454,0.00005149241,0.0009347277,0.0002927764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001552249,"about_ca_system_score_gemma":0.0003100591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004061069,"about_ca_topic_score_gemma":0.000004634083,"domain_scores_codex":[0.997661,0.0001325017,0.0009655583,0.0004109537,0.0003297394,0.0005002454],"domain_scores_gemma":[0.9985234,0.0002290392,0.0003271015,0.0005208135,0.0003047332,0.00009492284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009777765,0.00008280235,0.0004639424,0.00298638,0.0003747886,0.01176177,0.0004448918,7.066099e-9,0.0002766526,0.00005535092,0.9820788,0.001376844],"study_design_scores_gemma":[0.0009356531,0.0003069865,0.00002914628,0.0002138848,0.0003773604,0.117378,0.00004214881,0.00009255766,0.01011916,0.000377811,0.8698321,0.0002951594],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.003161954,0.0005962536,0.0002398755,0.9875241,0.0006315764,0.002964808,0.002832117,0.0001852543,0.001864069],"genre_scores_gemma":[0.8324063,0.000180859,0.0016925,0.06123155,0.001625468,0.004262161,0.08744191,0.0002529619,0.01090629],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9262925,"threshold_uncertainty_score":0.9998462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01380312685588859,"score_gpt":0.2886362493235503,"score_spread":0.2748331224676617,"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."}}