{"id":"W3033069241","doi":"10.1049/iet-gtd.2020.0389","title":"Credibility‐based secure distributed load frequency control for power systems under false data injection attacks","year":2020,"lang":"en","type":"article","venue":"IET Generation Transmission & Distribution","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Credibility; Computer science; Automatic frequency control; Computer security; Control (management); Power (physics); Electric power system; Reliability engineering; Engineering; Telecommunications; Artificial intelligence","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":[0.0003846595,0.0002931828,0.0002968614,0.00002912811,0.0003056766,0.0001552177,0.000312354,0.0003146403,0.00006250829],"category_scores_gemma":[0.0001274247,0.000278118,0.00011554,0.0003554909,0.00005293917,0.0004761766,0.00001302963,0.0002568319,0.00001472675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002507762,"about_ca_system_score_gemma":0.0001708886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002249968,"about_ca_topic_score_gemma":0.00001778307,"domain_scores_codex":[0.9979258,0.0001213743,0.000564191,0.0005915393,0.0004486014,0.000348517],"domain_scores_gemma":[0.9987769,0.00007814794,0.00008366205,0.0004750872,0.000301405,0.0002848406],"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":[0.0001870429,0.0001229704,0.0001827586,0.0003555318,0.000069647,0.000003073975,0.0002138818,0.8287063,0.1135675,0.001014206,0.05480102,0.0007760871],"study_design_scores_gemma":[0.001661211,0.0001743193,0.0003479548,0.0000465657,0.00007533436,0.000003307979,0.00007494873,0.9534963,0.007709356,0.00006359141,0.03601732,0.0003297795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03005397,0.001132143,0.9552134,0.001968356,0.001153473,0.0009724313,0.009019258,0.0004688574,0.00001808672],"genre_scores_gemma":[0.9757496,0.00004483755,0.0003084602,0.0002051981,0.0004399491,0.00009308801,0.02312448,0.00002982867,0.00000458697],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.954905,"threshold_uncertainty_score":0.9999671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03906685109084698,"score_gpt":0.2571185389994423,"score_spread":0.2180516879085953,"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."}}