{"id":"W7125896246","doi":"10.1109/inspect67393.2025.11350544","title":"A Stacked Ensemble of Attention-Augmented Deep Learning Models for Robust Anomaly Detection in Smart Grids","year":2025,"lang":"","type":"article","venue":"","topic":"Electricity Theft Detection Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Interpretability; Deep learning; Anomaly detection; Ensemble learning; Boosting (machine learning); Smart grid; Convolutional neural network; Gradient boosting; Grid","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":[0.0007503419,0.0007825926,0.0007628811,0.0004579157,0.0002622243,0.0004759886,0.001051017,0.0005908002,0.0008164634],"category_scores_gemma":[0.001229226,0.0003315655,0.0005635276,0.0004225576,0.0002474895,0.0009750131,0.000785812,0.001078045,0.0003292023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004800789,"about_ca_system_score_gemma":0.0007555553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008929705,"about_ca_topic_score_gemma":0.01444118,"domain_scores_codex":[0.9997739,0.00004541928,0.00001028166,0.00006251616,0.00006174919,0.0000461737],"domain_scores_gemma":[0.9996841,0.00009766901,0.00003385735,0.00004450223,0.0001164888,0.00002350364],"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":[0.0001342364,0.0001188926,0.002995168,0.00003101133,0.000129658,0.00008192533,0.00005010188,0.7598644,0.006631615,0.002309358,0.002819865,0.2248337],"study_design_scores_gemma":[0.000001108169,0.00001116834,0.0001144708,0.000001251472,0.000006970814,0.000004397175,0.00000169996,0.9987857,0.0004897553,0.0004621362,0.0001194992,0.000001786291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.117973,0.001034272,0.8750571,0.0003476982,0.0001267098,0.00003100794,0.0001705089,0.003047814,0.002211731],"genre_scores_gemma":[0.9310668,0.0002423364,0.06485713,0.0001582218,0.00006656006,0.00003081934,0.000409392,0.00008034436,0.003088462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008929705,"threshold_uncertainty_score":0.01775545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0145842821189494,"score_gpt":0.2286201274990934,"score_spread":0.214035845380144,"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."}}