{"id":"W4409573367","doi":"10.61091/jcmcc127a-026","title":"Application of Time Series Analysis Model in Monitoring Electricity Consumption Behaviour and Anti-Theft of Electricity","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Technology and Security Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity; Consumption (sociology); Series (stratigraphy); Time series; Environmental economics; Business; Computer science; Economics; Engineering; Electrical engineering; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008888227,0.0006525472,0.0006344682,0.001033817,0.0002869318,0.0006648485,0.0006223242,0.0005113074,0.0006581173],"category_scores_gemma":[0.002281873,0.0002100569,0.0006456169,0.0008502639,0.0002368711,0.0008568791,0.0003288413,0.000728319,0.0001933326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005545613,"about_ca_system_score_gemma":0.0007463778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009225949,"about_ca_topic_score_gemma":0.006500767,"domain_scores_codex":[0.9994844,0.0001351144,0.00004100956,0.0001521896,0.0001507617,0.00003649334],"domain_scores_gemma":[0.9991838,0.0003694867,0.0001201715,0.00007253433,0.0002247008,0.00002930618],"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":[0.0001420985,0.0003137139,0.01481193,0.0001330297,0.0002417739,0.000151779,0.0001519462,0.7506719,0.006522698,0.00385843,0.002317595,0.2206831],"study_design_scores_gemma":[0.000001486055,0.00001374313,0.0008901336,0.000002009578,0.000005746339,0.00001125155,0.00000659856,0.9980987,0.0005293849,0.0003262791,0.0001114211,0.000003394759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1632555,0.0004646017,0.8316652,0.0003702278,0.00009232104,0.0000751746,0.0002294585,0.001131795,0.002715764],"genre_scores_gemma":[0.9406335,0.0002391142,0.05714474,0.00005349793,0.00003373094,0.00007939417,0.0003245889,0.00003334045,0.001458064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009225949,"threshold_uncertainty_score":0.01834446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008511268933939064,"score_gpt":0.2525940449864108,"score_spread":0.2440827760524718,"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."}}