{"id":"W3003436024","doi":"10.1109/pesgm40551.2019.8973679","title":"Advanced Cyber-Physical Attack Classification with Extreme Gradient Boosting for Smart Transmission Grids","year":2019,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Smart grid; Testbed; Cyber-physical system; Classifier (UML); Boosting (machine learning); Real-time computing; Data mining; Machine learning; Artificial intelligence; Computer network; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.002094928,0.0006347761,0.001204462,0.00086567,0.0003946264,0.000740051,0.0008442746,0.0006911811,0.0006288958],"category_scores_gemma":[0.002037868,0.0002238927,0.0006406402,0.0006684752,0.0003640981,0.0008787166,0.0007259824,0.001114619,0.000317428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004405895,"about_ca_system_score_gemma":0.0004676768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001889919,"about_ca_topic_score_gemma":0.001360639,"domain_scores_codex":[0.9993469,0.00021816,0.00003432104,0.00009739576,0.0002034305,0.00009968452],"domain_scores_gemma":[0.9993253,0.0002508338,0.00006665447,0.00008575089,0.0002256414,0.00004587241],"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":[0.000439836,0.0004188214,0.009120182,0.00007700164,0.0001533209,0.000158838,0.00008515717,0.6105552,0.006931172,0.002560374,0.006239049,0.363261],"study_design_scores_gemma":[0.00000448931,0.00003517564,0.0006237142,0.000002807196,0.000005883246,0.00001368617,0.000006280392,0.9971457,0.0008840166,0.0008993716,0.00037575,0.000003146961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1846274,0.001202123,0.8082433,0.0005775304,0.000268698,0.0001390604,0.0001765458,0.00173609,0.003029229],"genre_scores_gemma":[0.9342246,0.0002152752,0.06342322,0.000154182,0.00009679072,0.00005998717,0.0003475013,0.00004449976,0.001433922],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002094928,"threshold_uncertainty_score":0.01107913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259664475773732,"score_gpt":0.235662646272295,"score_spread":0.2130660015145577,"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."}}