{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000966838,0.0001547927,0.0002158284,0.00008269013,0.00009922023,0.0000639477,0.0002023893,0.0001215233,0.0001897079],"category_scores_gemma":[0.0001125696,0.0001495202,0.0000643477,0.0005250996,0.00003195481,0.0003612036,0.00003350981,0.0003276189,0.00001632104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003198691,"about_ca_system_score_gemma":0.00001532016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003255325,"about_ca_topic_score_gemma":0.0001165398,"domain_scores_codex":[0.9986221,0.0001489596,0.0003105737,0.0003157792,0.0002492766,0.0003533717],"domain_scores_gemma":[0.9993817,0.00003035632,0.00002146703,0.0003834555,0.00005012991,0.0001328574],"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":[0.00001880982,0.00004113541,0.00286,0.00001291124,0.000007092181,3.865858e-7,0.0001791398,0.9211195,0.003739474,0.0002745323,0.0002209493,0.0715261],"study_design_scores_gemma":[0.0001570433,0.00002290081,0.02656101,0.00001768528,0.00001776538,0.000002196717,0.00004943923,0.9709226,0.001257062,0.0004596399,0.0003618399,0.0001708117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6769534,0.00002721526,0.3206625,0.00005765708,0.00007752881,0.0001544314,0.000004473977,0.0001044065,0.001958468],"genre_scores_gemma":[0.992878,0.0000126721,0.006590261,0.00003740475,0.0003399386,0.00003477095,0.00008723529,0.00001348399,0.000006252344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3159246,"threshold_uncertainty_score":0.6097255,"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."}}