{"id":"W7009552529","doi":"","title":"An evidential reasoning approach to evaluate intrusion vulnerability in distribution networks","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"American Water Works Association Research Foundation","keywords":"Intrusion; Inference; Vulnerability (computing); Bayesian network; Mains electricity; Vulnerability assessment; Bayesian inference; Evidential reasoning approach","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009195714,0.001276118,0.00116302,0.003728095,0.0009170674,0.003437635,0.002252741,0.001579738,0.003126831],"category_scores_gemma":[0.02710832,0.0005352961,0.001848946,0.002218465,0.002581975,0.004865775,0.002309721,0.002031997,0.0002144287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00295834,"about_ca_system_score_gemma":0.002441154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005625606,"about_ca_topic_score_gemma":0.004942289,"domain_scores_codex":[0.994881,0.002512513,0.0004815134,0.0004765242,0.001416186,0.0002322192],"domain_scores_gemma":[0.9860547,0.01130605,0.00095971,0.0003751666,0.001062122,0.0002422925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001012102,0.0001014356,0.003596034,0.0002204897,0.0002119125,0.0004851353,0.0004713807,0.682116,0.001224876,0.2658425,0.0007375406,0.04489162],"study_design_scores_gemma":[0.00002646977,0.00008612122,0.0006285312,0.00005278339,0.00007896343,0.00009101437,0.0001412995,0.8328549,0.0007847407,0.1638225,0.001407252,0.00002534247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02537891,0.0003967303,0.9669119,0.0004445026,0.00003301534,0.0001754829,0.0001856731,0.00009936737,0.006374431],"genre_scores_gemma":[0.6208167,0.000391569,0.3765547,0.00008750008,0.0000624528,0.0002287994,0.000222553,0.00001858543,0.001617159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009195714,"threshold_uncertainty_score":0.04863214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00873667116316832,"score_gpt":0.261083869143786,"score_spread":0.2523471979806176,"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."}}