{"id":"W4226052266","doi":"10.5267/j.ijdns.2022.1.010","title":"Artificial intelligence for target symptoms of Thai herbal medicine by web scraping","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Walailak University","keywords":"Artificial intelligence; The Internet; Computer science; Medical knowledge; Trustworthiness; Machine learning; Traditional medicine; Medical education; World Wide Web; Medicine; Internet privacy","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":[],"consensus_categories":[],"category_scores_codex":[0.00286957,0.00007553077,0.0001522432,0.0001836636,0.0002054568,0.0001125113,0.005154527,0.00001550205,0.00001921838],"category_scores_gemma":[0.0002513904,0.00006018766,0.00002456085,0.0005374078,0.0003358015,0.001403969,0.001552261,0.0001807965,1.119073e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004999764,"about_ca_system_score_gemma":0.0002277791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006871735,"about_ca_topic_score_gemma":0.00000110367,"domain_scores_codex":[0.9981145,0.00003552751,0.0004682235,0.0002540473,0.0009540362,0.0001737086],"domain_scores_gemma":[0.9986098,0.0001974689,0.0005012621,0.0002599523,0.0003640546,0.00006740828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001480033,0.000121354,0.0007225366,0.00001642875,0.00006678417,0.00003201205,0.0009115858,0.0007442932,0.02732917,0.1191353,0.02103917,0.8297333],"study_design_scores_gemma":[0.0002990739,0.001223522,0.0000399549,0.0003245056,0.00002203088,0.0005965173,0.0002874659,0.6042584,0.01610786,0.3522603,0.02426946,0.0003108805],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00388314,0.004832555,0.9865159,0.003352573,0.001225954,0.00007080584,0.00006486013,0.0000191096,0.00003510876],"genre_scores_gemma":[0.7352458,0.0000711442,0.2639802,0.0003704357,0.0003097768,0.000001933961,0.000009941533,0.000003122408,0.000007660719],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8294224,"threshold_uncertainty_score":0.9578479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03440612293390766,"score_gpt":0.3426756939727749,"score_spread":0.3082695710388673,"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."}}