{"id":"W4361015898","doi":"10.2196/40805","title":"Visualization of Traditional Chinese Medicine Formulas: Development and Usability Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Traditional Chinese Medicine Studies","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visualization; Usability; Computer science; Traditional Chinese medicine; Flexibility (engineering); Traditional medicine; Mathematics; Data mining; Medicine; Human–computer interaction; Alternative medicine; Statistics","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":[0.01377002,0.001334721,0.0009350298,0.002397707,0.000788548,0.002063087,0.001340236,0.0009622789,0.001982176],"category_scores_gemma":[0.03533769,0.0004669339,0.001419404,0.001677025,0.0006284084,0.002074158,0.001847372,0.0006417054,0.0002811749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000908173,"about_ca_system_score_gemma":0.001056614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001843442,"about_ca_topic_score_gemma":0.001593348,"domain_scores_codex":[0.9935216,0.004206331,0.0005259769,0.000547016,0.0009250942,0.0002739266],"domain_scores_gemma":[0.9691162,0.02207501,0.0007120123,0.001573171,0.005839116,0.000684526],"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":[0.002032941,0.004471402,0.0604067,0.008565746,0.000559447,0.003312162,0.1082128,0.005862558,0.08475749,0.002806047,0.00947288,0.7095398],"study_design_scores_gemma":[0.003319162,0.02834034,0.286241,0.006684591,0.002697489,0.01051508,0.1005418,0.2376188,0.1757949,0.007472296,0.1391653,0.001609317],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.907152,0.001190805,0.0821034,0.0005014794,0.00008917021,0.003220176,0.0003505675,0.002072438,0.00331977],"genre_scores_gemma":[0.8347089,0.001045657,0.1591622,0.0001635701,0.000052218,0.002401678,0.0006826188,0.0003366646,0.001446491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01377002,"threshold_uncertainty_score":0.07282376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.151729952927381,"score_gpt":0.4706573920989386,"score_spread":0.3189274391715575,"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."}}