{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003052687,0.0006929355,0.0004737604,0.0007167476,0.0003410872,0.000532032,0.0007392548,0.0006993642,0.002142353],"category_scores_gemma":[0.007647195,0.000173611,0.0006326884,0.0004239609,0.0004654987,0.0007142581,0.000628133,0.0004210632,0.0006069775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104311,"about_ca_system_score_gemma":0.000810546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008003933,"about_ca_topic_score_gemma":0.003057985,"domain_scores_codex":[0.9990723,0.0003517978,0.0001071774,0.0001380018,0.0002508906,0.00007970281],"domain_scores_gemma":[0.9956467,0.001983131,0.0002053822,0.0004761988,0.001577306,0.0001113509],"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":[0.006089166,0.009643554,0.2519224,0.002975342,0.001435786,0.001512486,0.001687914,0.2321675,0.03445163,0.003278516,0.009862127,0.4449737],"study_design_scores_gemma":[0.0004375968,0.007384882,0.08950596,0.0001121139,0.000392567,0.000526602,0.0004946636,0.8758007,0.02033206,0.0008447255,0.004091563,0.00007661945],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836529,0.0004090615,0.01250834,0.0001059723,0.00005363033,0.0005607301,0.0004584864,0.0002124352,0.002038492],"genre_scores_gemma":[0.9917055,0.0001573551,0.006070093,0.00003785227,0.00001147508,0.0002096055,0.0009449698,0.000007142859,0.0008559122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008003933,"threshold_uncertainty_score":0.01614434,"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."}}