{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006540097,0.000231957,0.0002168379,0.0004506621,0.001156102,0.00139837,0.0003275959,0.0009764392,0.01088353],"category_scores_gemma":[0.001676799,0.0001320944,0.0001573828,0.0003735489,0.002714475,0.001056013,0.0004685196,0.000791759,0.002368366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009578085,"about_ca_system_score_gemma":0.001012893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00273258,"about_ca_topic_score_gemma":0.002152815,"domain_scores_codex":[0.9995815,0.00006640307,0.00001634351,0.0000878913,0.0002039636,0.0000438128],"domain_scores_gemma":[0.9992154,0.0002425539,0.0001290428,0.00006110515,0.0002569708,0.00009501228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002033745,0.0001876082,0.004510149,0.0005899945,0.0000412901,0.0008175708,0.001607495,0.0009296216,0.02266245,0.7584816,0.03116445,0.1788044],"study_design_scores_gemma":[0.00004207532,0.0003399141,0.01218606,0.0001669089,0.00009140805,0.002338068,0.001833249,0.002042324,0.05936525,0.261391,0.6601223,0.00008156754],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.135244,0.01997334,0.04728753,0.02560103,0.002736331,0.0002263015,0.0005865357,0.0002452355,0.7680997],"genre_scores_gemma":[0.8134543,0.01125888,0.01980406,0.002999358,0.002143497,0.0001458825,0.0002066193,0.00005171013,0.1499358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01088353,"threshold_uncertainty_score":0.03640908,"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."}}