{"id":"W419485389","doi":"","title":"「変わる内部監査」から「変える内部監査」へ (特集 業務改善に活かす内部監査--内部統制・情報技術・不正防止への対応)","year":2008,"lang":"ja","type":"article","venue":"Accounting","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":[0.0006448739,0.0008306978,0.0008354005,0.0004263939,0.0009984453,0.0001158873,0.001005603,0.001041148,0.001043353],"category_scores_gemma":[0.0003168344,0.0009340587,0.000327052,0.0008938807,0.0004777684,0.001116992,0.0003000692,0.001634132,0.001850032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000175017,"about_ca_system_score_gemma":0.0001258841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005639483,"about_ca_topic_score_gemma":0.0001143992,"domain_scores_codex":[0.9959199,0.0000770221,0.001033186,0.0008893959,0.0005159245,0.001564582],"domain_scores_gemma":[0.9980237,0.000280276,0.0002087884,0.001147773,0.0001717674,0.0001676994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004237391,0.001566336,0.4519852,0.005608143,0.004855179,0.00760699,0.04328809,0.03107407,0.03977455,0.1799937,0.1564697,0.07735435],"study_design_scores_gemma":[0.01156193,0.001335091,0.3776503,0.003062708,0.001632556,0.005198725,0.0322662,0.1322302,0.02359865,0.05157517,0.3429086,0.01697983],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8155652,0.01346642,0.0004838775,0.0005449541,0.00224457,0.0004010502,0.00004814081,0.001988738,0.1652571],"genre_scores_gemma":[0.9925551,0.001747003,0.001941449,0.0002691463,0.001004986,0.00003795694,0.00004699771,0.0001615225,0.00223587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1864389,"threshold_uncertainty_score":0.9998698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201208805186526,"score_gpt":0.2004281490531616,"score_spread":0.1884160610012963,"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."}}