{"id":"W2691163440","doi":"","title":"「高齢化社会における心房細動マネジメント」：1次予防，2次予防の立場から見たアピキサバンの位置づけ","year":2015,"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008904146,0.00031868,0.000261263,0.0007556241,0.00153837,0.001809016,0.0003879056,0.0008120438,0.01204027],"category_scores_gemma":[0.001417635,0.000254734,0.0003622889,0.0004615023,0.00174255,0.001079235,0.0004957743,0.0009667303,0.003425393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008859108,"about_ca_system_score_gemma":0.001543255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002556853,"about_ca_topic_score_gemma":0.002306356,"domain_scores_codex":[0.9993371,0.0001059656,0.00003976726,0.000146477,0.000272487,0.00009817928],"domain_scores_gemma":[0.99896,0.0002436526,0.0001758111,0.0001101746,0.0004080495,0.0001023174],"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":[0.0007589047,0.0004784641,0.02277627,0.001052262,0.0001930389,0.002733166,0.005114775,0.003091848,0.2657605,0.2929896,0.01834013,0.3867111],"study_design_scores_gemma":[0.0000816243,0.001111206,0.05300352,0.0002833499,0.0002561489,0.005411521,0.006686707,0.003880104,0.3689831,0.1249069,0.4351437,0.0002521539],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.3841709,0.01023677,0.05995607,0.005529223,0.001589002,0.0003824148,0.0006356471,0.0003774226,0.5371225],"genre_scores_gemma":[0.8827041,0.003951692,0.02376008,0.0011693,0.0004755674,0.0001368463,0.0003045519,0.00005875524,0.08743913],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.01204027,"threshold_uncertainty_score":0.04027867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03095460649644113,"score_gpt":0.2740437244058697,"score_spread":0.2430891179094286,"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."}}