{"id":"W4408762917","doi":"10.1007/s00202-025-03044-4","title":"Enhancing electricity theft detection with ADASYN-enhanced machine learning models","year":2025,"lang":"en","type":"article","venue":"Electrical Engineering","topic":"Electricity Theft Detection Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Electricity; Computer science; Engineering; Computer security; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002706537,0.0004372675,0.0004293055,0.0008830437,0.0001823018,0.00007824332,0.000260252,0.0002394756,0.00001273282],"category_scores_gemma":[0.0001645241,0.0004364515,0.0001086508,0.002884718,0.0000162971,0.0003255315,0.00003320456,0.001430702,0.000009847864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006549262,"about_ca_system_score_gemma":0.00004571207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006065091,"about_ca_topic_score_gemma":0.00006134849,"domain_scores_codex":[0.9979945,0.00004443189,0.0004297444,0.0004155025,0.0003084141,0.0008073694],"domain_scores_gemma":[0.9992262,0.0002282952,0.00005044806,0.0002821291,0.00009650105,0.0001164174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003398103,0.00002057668,0.00001331359,0.00007689765,0.00009807613,0.000004691477,0.00003965493,0.4127724,0.5550957,0.0005297709,0.00001688337,0.03129805],"study_design_scores_gemma":[0.0001899666,0.0001277059,0.00002509097,0.00004385539,0.00002058247,0.00001229102,0.000001891215,0.4939112,0.5045297,0.000184995,0.0006972455,0.0002554593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04144245,0.001285431,0.9466099,0.00001305562,0.0001347688,0.00033853,8.587854e-7,0.005239195,0.004935871],"genre_scores_gemma":[0.9946256,0.000284724,0.004195356,0.0000360337,0.00007585136,0.0001349419,0.000003765822,0.0001091536,0.000534573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9531832,"threshold_uncertainty_score":0.9998087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003744233733347096,"score_gpt":0.1796297673908979,"score_spread":0.1758855336575509,"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."}}