{"id":"W2175176996","doi":"10.1155/2015/460490","title":"Bioinformatics/Medical Informatics in Traditional Medicine and Integrative Medicine","year":2015,"lang":"en","type":"editorial","venue":"The Scientific World JOURNAL","topic":"Traditional Chinese Medicine Studies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Health informatics; Informatics; Computer science; Integrative medicine; Data science; Translational research informatics; Precision medicine; Alternative medicine; Medicine; Bioinformatics; Health Administration Informatics; Biology; Pathology; Public health; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007502477,0.0008499322,0.001536629,0.006592026,0.001500636,0.008651716,0.001964545,0.003977987,0.02720831],"category_scores_gemma":[0.02265076,0.00058924,0.001140982,0.01135466,0.003102253,0.008486571,0.005012255,0.005045187,0.02029809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649534,"about_ca_system_score_gemma":0.003274025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000828777,"about_ca_topic_score_gemma":0.0006308802,"domain_scores_codex":[0.9902408,0.005000483,0.001026715,0.00117738,0.002246709,0.0003078579],"domain_scores_gemma":[0.9838428,0.0101597,0.001091566,0.001904111,0.002029001,0.0009728406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001635482,0.0002005314,0.002896318,0.004174835,0.0001640917,0.000697196,0.001443548,0.001556939,0.003288271,0.2018782,0.2362991,0.5472373],"study_design_scores_gemma":[0.00004597527,0.00007604224,0.002483117,0.001534812,0.00005947078,0.001640315,0.0006015631,0.004975815,0.00181179,0.1681585,0.8185404,0.0000722823],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"editorial","genre_scores_codex":[0.009460503,0.1463376,0.43867,0.1575971,0.01661953,0.001234653,0.008807828,0.01199091,0.2092819],"genre_scores_gemma":[0.1256363,0.1842828,0.4867013,0.07159368,0.03043946,0.002221398,0.01619457,0.00233608,0.08059428],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.02720831,"threshold_uncertainty_score":0.09102082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05500239192348074,"score_gpt":0.3280678418428277,"score_spread":0.2730654499193469,"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."}}