{"id":"W4399455542","doi":"10.2196/48811","title":"Efficacy of an Artificial Intelligence App (Aysa) in Dermatological Diagnosis: Cross-Sectional Analysis","year":2024,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Cross-sectional study; Sunscreening Agents; Dermatology; Medicine; Computer science; World Wide Web; Pathology; Skin cancer","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":[0.008501651,0.00027102,0.0004943049,0.001039377,0.0005954825,0.001133438,0.0004916956,0.0007128865,0.001631084],"category_scores_gemma":[0.02545374,0.0004064181,0.001076161,0.0006135657,0.0006180762,0.001190315,0.0007497254,0.001145143,0.0005198692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004629305,"about_ca_system_score_gemma":0.0004414881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490158,"about_ca_topic_score_gemma":0.001384092,"domain_scores_codex":[0.9957995,0.001991304,0.0006262679,0.0004986552,0.0008504102,0.0002338365],"domain_scores_gemma":[0.96393,0.02128613,0.007932354,0.001218678,0.004487785,0.001145167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004773937,0.0009098198,0.9930909,0.0001101086,0.000128183,0.0001216888,0.001664641,0.00007325804,0.0001990527,0.00002736832,0.0001719776,0.003025577],"study_design_scores_gemma":[0.00004260546,0.006985573,0.9839389,0.0001041449,0.0002638012,0.0008566636,0.004820751,0.001370966,0.0006461754,0.00004027826,0.0009011945,0.00002908389],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992072,0.000118057,0.00009072237,0.00003178711,0.000006258614,0.0001015301,0.0001370341,0.00000362905,0.0003037351],"genre_scores_gemma":[0.9992303,0.0001027901,0.0002252362,0.00004780989,0.00000819129,0.0000934432,0.0001432533,0.000002969556,0.0001460885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008501651,"threshold_uncertainty_score":0.04496157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03916212260616856,"score_gpt":0.3648515988482846,"score_spread":0.325689476242116,"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."}}