{"id":"W2969076975","doi":"10.1097/cm9.0000000000000372","title":"Artificial intelligence in dermatology","year":2019,"lang":"en","type":"article","venue":"Chinese Medical Journal","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Dermatology; Medicine; Traditional medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001529211,0.000748586,0.0007667596,0.001647756,0.001037344,0.004762632,0.001145544,0.005112262,0.02813159],"category_scores_gemma":[0.00556038,0.0002216325,0.0005386452,0.001686127,0.005007915,0.003344773,0.002236272,0.005129284,0.009725347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002762237,"about_ca_system_score_gemma":0.002226626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002129743,"about_ca_topic_score_gemma":0.001791758,"domain_scores_codex":[0.9979971,0.0007676496,0.0001306003,0.0003651997,0.0006089818,0.0001303623],"domain_scores_gemma":[0.9977667,0.001270225,0.000194066,0.0001665469,0.00038268,0.0002197978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004576753,0.00007554957,0.001294854,0.0009736492,0.00003488112,0.0005199416,0.0006612859,0.001069421,0.000371146,0.4420132,0.2303059,0.3226344],"study_design_scores_gemma":[0.000009887272,0.00003563611,0.000896599,0.0009460634,0.000008896368,0.001393636,0.0002853855,0.0003533174,0.0001195389,0.1777069,0.8182214,0.00002267142],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.002584981,0.436954,0.01431888,0.1500892,0.01618697,0.0001055795,0.0004663623,0.0002840836,0.3790101],"genre_scores_gemma":[0.1417108,0.4723555,0.02350386,0.09906392,0.02909094,0.0003471211,0.0009337192,0.0002448041,0.2327493],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02813159,"threshold_uncertainty_score":0.09410959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01243081056420168,"score_gpt":0.2973502561920688,"score_spread":0.2849194456278671,"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."}}