{"id":"W4410358682","doi":"10.1109/tsg.2025.3569783","title":"A New Method for Stealthy False Data Injection Attack Detection Using Advanced Feasibility Areas Considering Spatial Distribution","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Resources Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Distribution (mathematics); Reliability engineering; Data mining; Real-time computing; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00077469,0.000250511,0.000290549,0.0002274641,0.0008835171,0.0001807294,0.0004773368,0.0001916222,0.0000153098],"category_scores_gemma":[0.00006222261,0.0002782006,0.0001492031,0.0009010597,0.00003401259,0.001168883,0.00002092521,0.0004014575,0.000007528591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004672705,"about_ca_system_score_gemma":0.0002878578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001322764,"about_ca_topic_score_gemma":0.003902675,"domain_scores_codex":[0.997681,0.0002561147,0.0005056451,0.0009302284,0.0002609802,0.0003659988],"domain_scores_gemma":[0.9980218,0.0003446634,0.0001753467,0.001134095,0.0001859501,0.0001381399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006986599,0.000189415,0.00002365907,0.00007893017,0.00007260555,0.000001222141,0.0001131218,0.09030545,0.005267272,0.0001523575,0.0007124226,0.9023849],"study_design_scores_gemma":[0.001424074,0.0003598481,0.0002976512,0.00009567772,0.00007864596,0.00003659969,0.0000318554,0.9322024,0.05133228,0.001027804,0.01283137,0.0002817812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01937129,0.00003799461,0.9708741,0.0003677967,0.007864327,0.0009486112,0.0001518648,0.0003592131,0.00002478715],"genre_scores_gemma":[0.8999727,0.00003605896,0.09909227,0.0002581459,0.0003669625,0.00007810703,0.00005311333,0.00002044566,0.0001222125],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9021031,"threshold_uncertainty_score":0.999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06759788366009858,"score_gpt":0.3553683315114566,"score_spread":0.2877704478513581,"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."}}