{"id":"W3095989683","doi":"","title":"耐性菌感染予防策としての抗菌薬サイクリング/ミキシング 第2回 操薬から抗菌薬サイクリング/ミキシングを考える","year":2006,"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":"Computer 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":[0.0006954818,0.0008147069,0.0008408463,0.0004314644,0.0003560254,0.0000747224,0.001065317,0.000777005,0.006633379],"category_scores_gemma":[0.0001131114,0.000847943,0.0003325352,0.0007321015,0.0007470708,0.0004387742,0.00019153,0.001727413,0.002563871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001732133,"about_ca_system_score_gemma":0.0001498678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004693056,"about_ca_topic_score_gemma":0.0001025658,"domain_scores_codex":[0.9956458,0.0001539733,0.001070326,0.000821123,0.0007830176,0.001525716],"domain_scores_gemma":[0.9981566,0.000276029,0.000135826,0.0009498608,0.00009354052,0.0003881477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003636084,0.001398678,0.003817223,0.002350878,0.001699323,0.002826335,0.002508343,0.00570043,0.03002556,0.1378655,0.7421743,0.06926972],"study_design_scores_gemma":[0.009755981,0.0005552609,0.008259529,0.0008023102,0.001074025,0.0005998371,0.002005534,0.05831897,0.02329228,0.06249898,0.8286405,0.004196807],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.230414,0.0639215,0.003480435,0.006738614,0.008291025,0.001192316,0.000398213,0.004828074,0.6807358],"genre_scores_gemma":[0.9894242,0.003271192,0.0008981564,0.0003372098,0.001862114,0.00009260563,0.0001211165,0.0001477897,0.003845674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7590101,"threshold_uncertainty_score":0.9993972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01156588935498763,"score_gpt":0.2422935870358271,"score_spread":0.2307276976808394,"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."}}