{"id":"W3190826406","doi":"","title":"骨髄異形成症候群(MDS)診療の進歩と課題 HighリスクMDSの治療","year":2018,"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":[0.0004209506,0.0004283579,0.0004412056,0.0002147423,0.0002617488,0.00002994613,0.0007408896,0.0004926021,0.01340998],"category_scores_gemma":[0.0001288656,0.0004266582,0.0001287834,0.0004194995,0.0009716946,0.0002533512,0.0001440103,0.000931138,0.004730758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000758661,"about_ca_system_score_gemma":0.00009363888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007539681,"about_ca_topic_score_gemma":0.00003463398,"domain_scores_codex":[0.9976689,0.00007332799,0.000509071,0.0004810705,0.0004037764,0.0008638224],"domain_scores_gemma":[0.9987538,0.0001192855,0.00005977446,0.0006529344,0.00008854908,0.0003256334],"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":[0.0002621204,0.0004620278,0.0008966724,0.001136132,0.001655261,0.000921373,0.008039216,0.00008282186,0.01940661,0.08365695,0.7644352,0.1190456],"study_design_scores_gemma":[0.003215354,0.0007603519,0.00175543,0.0004297501,0.0004361358,0.000230215,0.001967151,0.02677086,0.02892819,0.01630853,0.9176596,0.001538422],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1781823,0.02758079,0.001701336,0.006469643,0.01260314,0.000569143,0.0001208547,0.003001427,0.7697714],"genre_scores_gemma":[0.9917918,0.002603704,0.0006633629,0.0004006352,0.002334167,0.00003056873,0.00002198325,0.00006595667,0.002087751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8136096,"threshold_uncertainty_score":0.9998185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01693120804620809,"score_gpt":0.2636234702159899,"score_spread":0.2466922621697818,"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."}}