{"id":"W593900295","doi":"","title":"次世代除細動器等のバイオニック医療機器 (特集 日本から革新的医療危機を!--METISの取り組みを中心に)","year":2007,"lang":"ja","type":"article","venue":"イザイ","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Metis; Computer science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006776779,0.0004430483,0.0004420561,0.0003103818,0.0001849808,0.00004256712,0.0005198757,0.0007983877,0.001578963],"category_scores_gemma":[0.00008300181,0.0004831793,0.0001830848,0.0005070575,0.0002669795,0.0002430091,0.00009523569,0.0009322152,0.001914091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042558,"about_ca_system_score_gemma":0.00003985728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001342356,"about_ca_topic_score_gemma":0.0002669863,"domain_scores_codex":[0.9976681,0.00003322433,0.0005854325,0.000454145,0.0002509631,0.001008066],"domain_scores_gemma":[0.9987363,0.0001898361,0.0000558274,0.000780491,0.00005280588,0.0001846924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002923473,0.0004761307,0.007544011,0.001120334,0.001093537,0.00217205,0.006901009,0.002465532,0.01587881,0.7853633,0.06375413,0.1129388],"study_design_scores_gemma":[0.00503993,0.001541281,0.1161288,0.0008508334,0.0005925861,0.0006332649,0.01580047,0.008194203,0.03581515,0.1386966,0.6711491,0.00555789],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2897597,0.01825377,0.006964155,0.0006711594,0.003031427,0.0004179719,0.00005072446,0.001717532,0.6791336],"genre_scores_gemma":[0.991776,0.0007849997,0.002332368,0.0001513132,0.0004499083,0.00001048367,0.00002018737,0.00007131924,0.004403436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7020163,"threshold_uncertainty_score":0.999762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008405497088131769,"score_gpt":0.2171236895565797,"score_spread":0.208718192468448,"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."}}