{"id":"W2925257126","doi":"","title":"喘息予防・管理ガイドライン2018－改訂のポイントを中心に－","year":2019,"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":[0.0003962115,0.0003827171,0.000488337,0.0001906757,0.00008960509,0.00002458697,0.0006382108,0.0004477986,0.02372247],"category_scores_gemma":[0.00006590259,0.0003822705,0.0001462341,0.0003161125,0.0002180631,0.0002606748,0.0001173178,0.001053702,0.01102743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006630518,"about_ca_system_score_gemma":0.00008137904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003654357,"about_ca_topic_score_gemma":0.000007851652,"domain_scores_codex":[0.997929,0.00006278419,0.0004484013,0.0004428991,0.0003924355,0.0007244414],"domain_scores_gemma":[0.9988561,0.00013885,0.00005551939,0.0006660267,0.0000408719,0.000242639],"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":[0.0004297156,0.0009648332,0.01790592,0.005781288,0.003929321,0.00122492,0.01068347,0.004360586,0.04896181,0.126018,0.6090634,0.1706767],"study_design_scores_gemma":[0.004908818,0.0005143191,0.003017115,0.0006119504,0.0004220437,0.0001898526,0.002887795,0.07646745,0.007918084,0.01065111,0.8905551,0.001856348],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3670253,0.02548999,0.0002244845,0.002586782,0.007885205,0.0008222157,0.00005935033,0.001432015,0.5944746],"genre_scores_gemma":[0.991117,0.003452334,0.0003623325,0.000332367,0.0003644233,0.00004638043,0.00002858999,0.00005967768,0.004236924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6240916,"threshold_uncertainty_score":0.9998629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272375705384765,"score_gpt":0.2489006395989784,"score_spread":0.2361768825451307,"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."}}