{"id":"W2897901010","doi":"","title":"求められる軟性内視鏡の洗浄・消毒・滅菌","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001431065,0.0002851597,0.0001947015,0.0007673213,0.001508703,0.003214266,0.0003823579,0.001043422,0.01302251],"category_scores_gemma":[0.001987268,0.0001831576,0.0002307028,0.0004225397,0.002775741,0.00164514,0.0007655902,0.001202539,0.004060263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001879271,"about_ca_system_score_gemma":0.002926178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003091693,"about_ca_topic_score_gemma":0.003112912,"domain_scores_codex":[0.9992158,0.0001383703,0.00004692609,0.0001154059,0.0003995434,0.00008389048],"domain_scores_gemma":[0.998768,0.0002781927,0.0001562678,0.0001106873,0.0005295821,0.0001572794],"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":[0.0001552866,0.0002575092,0.005436479,0.0004120625,0.0000529382,0.0006397193,0.002592109,0.001516969,0.02404215,0.6710129,0.01617688,0.2777051],"study_design_scores_gemma":[0.00003774057,0.0005794779,0.01363669,0.0003096712,0.00008684889,0.001577018,0.005208584,0.002247518,0.05262711,0.2265992,0.6969913,0.00009872439],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09951308,0.0113224,0.0423485,0.01742542,0.001789047,0.0002615033,0.0002114004,0.0002013429,0.8269272],"genre_scores_gemma":[0.727731,0.009044807,0.02534349,0.00366705,0.0009206231,0.0001149748,0.0001144907,0.00004947562,0.2330142],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01302251,"threshold_uncertainty_score":0.04356462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772030216248074,"score_gpt":0.2674092177864826,"score_spread":0.2496889156240019,"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."}}