{"id":"W3027346379","doi":"","title":"Medical Scope：人工膵臓様デバイスによる血糖管理の未来","year":2019,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Business; 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":[0.0007974547,0.0004154235,0.0005696182,0.0001966502,0.00009381001,0.00002499326,0.000988611,0.0007765217,0.0724511],"category_scores_gemma":[0.0002401101,0.0003996351,0.0001554755,0.0003664825,0.0003586537,0.0002471107,0.000193398,0.001684922,0.01170626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007372567,"about_ca_system_score_gemma":0.0002633437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005708906,"about_ca_topic_score_gemma":0.00001835635,"domain_scores_codex":[0.9969782,0.0000954509,0.0005890138,0.0005071762,0.0009909003,0.0008392379],"domain_scores_gemma":[0.9984708,0.0002303084,0.00005512466,0.0006593114,0.00004244272,0.0005420551],"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":[0.0003660003,0.0009898191,0.009210246,0.005953379,0.003027684,0.003705739,0.005694867,0.001036859,0.0100341,0.1160773,0.5984493,0.2454546],"study_design_scores_gemma":[0.008223781,0.0005897818,0.002285576,0.002050363,0.0003713924,0.0006431253,0.002070619,0.095851,0.006689923,0.006710749,0.8722233,0.002290413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2830485,0.05392413,0.0003793811,0.007045581,0.009300452,0.0006889728,0.00004808123,0.001569341,0.6439955],"genre_scores_gemma":[0.9846228,0.01110634,0.0002039769,0.0007732828,0.0006475325,0.00002556449,0.00002867338,0.00006540676,0.00252638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7015743,"threshold_uncertainty_score":0.9998456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123130734711566,"score_gpt":0.2623126927252281,"score_spread":0.2499996192540715,"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."}}