{"id":"W2737178610","doi":"","title":"腎・心血管疾患の包括的治療戦略から糖尿病治療を考える：糖尿病と腎症","year":2013,"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":"Geography","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":[0.0002503299,0.0004037075,0.0004168183,0.0001858491,0.0001335959,0.00004827252,0.0006375189,0.0004358215,0.03219973],"category_scores_gemma":[0.0001068848,0.0003933858,0.0001365061,0.0003152177,0.0003507355,0.0004190757,0.0001119311,0.001036258,0.01245319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000609505,"about_ca_system_score_gemma":0.00006184599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003124457,"about_ca_topic_score_gemma":0.00001702187,"domain_scores_codex":[0.9978827,0.00006515545,0.00049818,0.0003931556,0.0003508141,0.0008100535],"domain_scores_gemma":[0.9988443,0.000136111,0.00005172004,0.0005486331,0.00006484672,0.000354405],"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":[0.00003002341,0.0003116107,0.001354924,0.001057852,0.001044714,0.0003208809,0.003723381,0.0004082109,0.01679303,0.0278932,0.822262,0.1248002],"study_design_scores_gemma":[0.007227829,0.0006668582,0.01295677,0.0009285734,0.0007819522,0.0004680915,0.007695863,0.1368539,0.02160171,0.07827593,0.7282989,0.004243552],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3080451,0.04282844,0.0009952128,0.01046633,0.006225526,0.001064991,0.00005894347,0.002657674,0.6276578],"genre_scores_gemma":[0.9930389,0.003162143,0.0006033288,0.000515066,0.0006084552,0.00008812426,0.00002148296,0.00005995941,0.001902547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6849938,"threshold_uncertainty_score":0.9998518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01429266572044755,"score_gpt":0.2452722987258974,"score_spread":0.2309796330054498,"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."}}