{"id":"W1983187427","doi":"10.1109/pesgm.2012.6344970","title":"EMS real time model enhancement and performance validation using archived telemetry and historical events data","year":2012,"lang":"en","type":"article","venue":"","topic":"Power Systems and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"EMS Ingénierie","keywords":"Computer science; Telemetry; Data modeling; Energy management system; Model validation; Reliability engineering; Data model (GIS); Real-time computing; Systems engineering; Engineering; Energy (signal processing); Energy management; Database; Telecommunications; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001156981,0.00007178986,0.00008939324,0.0000467559,0.00003465407,0.000008721332,0.00007944975,0.00003721093,0.000005656681],"category_scores_gemma":[0.000005503423,0.0000627003,0.000004682248,0.00002752933,0.000008414871,0.0003099787,0.0001266277,0.00004860678,0.000003863913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007364868,"about_ca_system_score_gemma":0.000003298504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000388355,"about_ca_topic_score_gemma":0.000001206024,"domain_scores_codex":[0.9995673,0.00000441456,0.0001110933,0.00009773345,0.00007109156,0.0001483898],"domain_scores_gemma":[0.999729,0.000008611483,0.0000157645,0.000206641,0.000004444049,0.00003547751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004655198,0.0002424031,0.2386524,0.001033842,0.0003134244,0.000002024611,0.002174029,0.006228978,0.5418668,0.001154681,0.01009679,0.198188],"study_design_scores_gemma":[0.0001093104,0.00001504803,0.003999918,0.00001818257,0.00001064643,0.000005340895,0.00001265822,0.9893878,0.005504539,0.0000288022,0.0007908217,0.0001169963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9422781,0.0002981433,0.05549832,0.000006893557,0.000113608,0.0000680004,0.000004326411,0.0001484135,0.001584124],"genre_scores_gemma":[0.9875724,0.0002393316,0.01181982,0.000001593836,0.0000304612,0.000002679958,0.0000115496,0.000008561456,0.0003136471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9831588,"threshold_uncertainty_score":0.2556844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0613126508121961,"score_gpt":0.2465180242681766,"score_spread":0.1852053734559805,"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."}}