{"id":"W6910375034","doi":"10.4224/21275252","title":"National Research Council Canada: 2010-11 to 2012-13 risk-based internal audit plan, internal audit, NRC April 2010-summary","year":2013,"lang":"en","type":"report","venue":"","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Internal audit; Chief audit executive; Treasury; Joint audit; Government (linguistics); Information technology audit; Audit","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01151784,0.001457935,0.001061941,0.006268283,0.006901517,0.008974391,0.004608699,0.004252319,0.01778841],"category_scores_gemma":[0.02363006,0.002165395,0.001077591,0.01349545,0.001239436,0.001648177,0.002465267,0.003651723,0.01008781],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1618841,"about_ca_system_score_gemma":0.6051738,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958155,"about_ca_topic_score_gemma":0.9973303,"domain_scores_codex":[0.9807727,0.0007118372,0.0009855051,0.0005810843,0.01346196,0.003486907],"domain_scores_gemma":[0.9455701,0.001195973,0.0008583363,0.0008455628,0.04618837,0.005341665],"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":[0.00008827157,0.0000986789,0.005193246,0.0002872272,0.00001771931,0.00007146788,0.0002243927,0.0004880586,0.0001258638,0.003650443,0.9778857,0.0118689],"study_design_scores_gemma":[0.0001086877,0.00005653112,0.1170127,0.0005927074,0.0000517745,0.00005850572,0.001344226,0.0006803796,0.000716141,0.0006202535,0.8786444,0.0001137151],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01237965,0.005373489,0.001830828,0.05720119,0.002706327,0.004498978,0.6548817,0.001710066,0.2594178],"genre_scores_gemma":[0.0317016,0.006868664,0.01049533,0.01219661,0.0002561877,0.002396628,0.2823608,0.00055906,0.653165],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8381159,"threshold_uncertainty_score":0.9720956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1452995941137731,"score_gpt":0.3494734199769277,"score_spread":0.2041738258631546,"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."}}