{"id":"W4412353324","doi":"10.1109/tie.2025.3581190","title":"Event-Triggered Entropy Learning for Encountering of FDI Attack in Grid-Connected Packed E-Cell Inverter","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Quantum-Dot Cellular Automata","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Inverter; Grid; Entropy (arrow of time); Computer science; Grid cell; Event (particle physics); Engineering; Mathematics; Electrical engineering; Physics; Voltage","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":[0.0002767314,0.0003149354,0.0003096006,0.0001481577,0.0001916484,0.0003342573,0.0005197466,0.0003412871,0.0008559647],"category_scores_gemma":[0.0008592731,0.0001451432,0.0002135444,0.0001050373,0.0003411303,0.0004230096,0.0004465669,0.0004495256,0.00008228063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003381868,"about_ca_system_score_gemma":0.0003417171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001804811,"about_ca_topic_score_gemma":0.00204205,"domain_scores_codex":[0.9998648,0.0000183204,0.00001092156,0.00003672317,0.00004741588,0.00002167454],"domain_scores_gemma":[0.9997289,0.0001018875,0.00005865578,0.00002546738,0.00006994796,0.00001515594],"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":[0.0003384359,0.0001343364,0.004472561,0.0001737811,0.0000630621,0.0002582611,0.0002025711,0.8131183,0.03871178,0.009139326,0.0008052542,0.1325823],"study_design_scores_gemma":[0.000004961425,0.0000464212,0.0002665606,0.000002598366,0.000005817202,0.00001235235,0.000004637201,0.9959876,0.003043186,0.0004914422,0.0001312839,0.000003067719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1347926,0.0002194168,0.8607724,0.0001607089,0.00005071243,0.0000470223,0.00002344162,0.0005599115,0.003373793],"genre_scores_gemma":[0.9894564,0.00005604536,0.009853341,0.00002768436,0.000005296457,0.00001984016,0.0000148948,0.000005379967,0.0005611154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001804811,"threshold_uncertainty_score":0.003588676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02406658699842337,"score_gpt":0.2650168866454318,"score_spread":0.2409502996470084,"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."}}