{"id":"W3168714507","doi":"","title":"エビデンスに基づいた漢方医療;各種疾患に対しての処方(1)過敏性腸症候群に対する桂枝加芍薬湯の効果","year":2007,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Political science","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":["insufficient_payload"],"category_scores_codex":[0.001243664,0.0005236139,0.0005285314,0.0003436753,0.0002209343,0.00003057618,0.0007847811,0.0006514622,0.007180266],"category_scores_gemma":[0.0001650151,0.0005445681,0.0001889124,0.0005664062,0.000480857,0.0002824068,0.000127455,0.001446132,0.00176715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001335974,"about_ca_system_score_gemma":0.00008758464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000812452,"about_ca_topic_score_gemma":0.00006004156,"domain_scores_codex":[0.9968265,0.00005420815,0.0007762801,0.0005231245,0.0005497659,0.001270071],"domain_scores_gemma":[0.9984279,0.0002345262,0.00008304711,0.0006819931,0.00006434052,0.0005082278],"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":[0.0007261198,0.001381519,0.006140642,0.002931152,0.003050552,0.006407713,0.0126126,0.0006826976,0.04804093,0.09522523,0.4072156,0.4155853],"study_design_scores_gemma":[0.005238303,0.0004681533,0.01009921,0.0006053665,0.0006338489,0.0005349179,0.005050623,0.01304863,0.04334985,0.01191885,0.9062797,0.002772502],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1976437,0.05299941,0.008334438,0.003173359,0.009064792,0.0007096998,0.00008002775,0.003032218,0.7249624],"genre_scores_gemma":[0.9920837,0.00346417,0.0008280305,0.0003829481,0.00135932,0.00001708014,0.00003197333,0.00008463222,0.00174818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.79444,"threshold_uncertainty_score":0.9997006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614283244887213,"score_gpt":0.2689159449684661,"score_spread":0.2527731125195939,"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."}}