{"id":"W4409603157","doi":"10.61091/jcmcc127b-094","title":"Research on deep learning-based fault diagnosis of power metering system","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Smart Grid and Power Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metering mode; Fault (geology); Deep learning; Computer science; Artificial intelligence; Electric power system; Power (physics); Reliability engineering; Engineering; Geology; Seismology; Mechanical engineering","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":[0.000514991,0.0005722179,0.0005207321,0.0006175184,0.0002126924,0.0006413929,0.0006659215,0.000668242,0.0006529966],"category_scores_gemma":[0.001433452,0.000288879,0.0004700551,0.0006100316,0.0004566949,0.001477647,0.0004037293,0.0009577445,0.0001294082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007617413,"about_ca_system_score_gemma":0.0008814314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007665533,"about_ca_topic_score_gemma":0.003404909,"domain_scores_codex":[0.9996759,0.00005195358,0.00002928957,0.0000895321,0.0001061694,0.00004717664],"domain_scores_gemma":[0.9995932,0.0001676969,0.00004740463,0.00003539918,0.000138357,0.00001797046],"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":[0.00008950678,0.00009018006,0.004135428,0.0002454176,0.000112382,0.0001024979,0.00009963828,0.66418,0.008106638,0.0129032,0.001548075,0.3083871],"study_design_scores_gemma":[0.000002568224,0.00001919006,0.0004611551,0.000007041274,0.000009079634,0.00001764878,0.000006401945,0.9949654,0.001788699,0.002255948,0.0004629048,0.000003904841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0522093,0.004063641,0.9386859,0.0008581596,0.0001271557,0.00002793037,0.00007325497,0.0006640595,0.003290564],"genre_scores_gemma":[0.9382075,0.003409536,0.05444987,0.0002213053,0.0001222041,0.00003262986,0.0001886561,0.00002931154,0.003338865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007665533,"threshold_uncertainty_score":0.01524186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01778631225507771,"score_gpt":0.2805411991321871,"score_spread":0.2627548868771094,"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."}}