{"id":"W3017092352","doi":"10.2196/17608","title":"Artificial Intelligence–Based Traditional Chinese Medicine Assistive Diagnostic System: Validation Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Traditional Chinese Medicine Studies","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer science; Variety (cybernetics); Process (computing); Expert system; Convolutional neural network; Machine learning","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007011974,0.0004153744,0.0009236097,0.0002465676,0.0002083147,0.00002374592,0.0002682132,0.0001664987,0.001090069],"category_scores_gemma":[0.00814492,0.0002737776,0.0001491909,0.0009617418,0.0005118386,0.0002242886,0.00006487736,0.0007801847,0.0002938526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001754223,"about_ca_system_score_gemma":0.0004167628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001260104,"about_ca_topic_score_gemma":0.000004700599,"domain_scores_codex":[0.9945242,0.0001160091,0.001708338,0.000266207,0.003032861,0.0003523781],"domain_scores_gemma":[0.995762,0.002303059,0.0003226438,0.0002762525,0.0003456904,0.0009903711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006262191,0.02108555,0.4339752,0.02496882,0.004967054,0.0067184,0.1954163,0.001533621,0.0002939782,0.0533467,0.1526485,0.09878369],"study_design_scores_gemma":[0.008076927,0.01506552,0.6805683,0.004139962,0.001533608,0.0005912259,0.06794834,0.2173342,0.0001972203,0.001831411,0.001368021,0.001345216],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172713,0.00009429081,0.03436406,0.03491481,0.001009224,0.003115865,0.0001039841,0.0006770738,0.008449418],"genre_scores_gemma":[0.9901419,0.000007245812,0.0007741448,0.004872612,0.003217828,0.0003438977,0.0006026707,0.00003136957,0.000008391022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2465932,"threshold_uncertainty_score":0.9999714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08157051738527261,"score_gpt":0.3433318139802479,"score_spread":0.2617612965949753,"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."}}