{"id":"W4405372779","doi":"10.23977/jeeem.2024.070310","title":"Application of artificial intelligence in electric power dispatching automation system","year":2024,"lang":"en","type":"article","venue":"Journal of Electrotechnology Electrical Engineering and Management","topic":"Power Systems and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automation; Computer science; Electric power; Process automation system; Artificial intelligence; Power (physics); Electric power system; Engineering; Systems engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003140814,0.0001388669,0.0002761186,0.001404605,0.00001416284,0.00002277323,0.0001734711,0.0001429757,4.602844e-7],"category_scores_gemma":[0.00002637995,0.0001271883,0.00005328087,0.001215176,0.00001313237,0.00009908633,0.00002451441,0.0004741115,0.000001454213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002158214,"about_ca_system_score_gemma":0.0000096813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004215103,"about_ca_topic_score_gemma":8.955008e-7,"domain_scores_codex":[0.9989,0.000009216214,0.0005580919,0.0001298743,0.0001407545,0.0002620554],"domain_scores_gemma":[0.9997187,0.00004583063,0.00006694716,0.0001184207,0.00002441205,0.00002568871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000146092,0.0000385758,0.00001950082,0.001021476,0.0002119089,0.0001154598,0.00005594613,0.05494635,0.07313024,0.4711455,0.00004543086,0.399255],"study_design_scores_gemma":[0.00005351951,0.0002126406,0.0001638418,0.000240492,0.00003022998,0.0001861975,0.00004223648,0.9753168,0.02104402,0.001908907,0.0006714629,0.0001296952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1166299,0.007564484,0.8746617,0.00009769126,0.0001855675,0.0001976662,3.361573e-7,0.0005716352,0.00009100611],"genre_scores_gemma":[0.9966118,0.0008007531,0.002519018,0.000001441178,0.00001962857,0.00002528669,2.708584e-7,0.00001968935,0.000002090105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9203704,"threshold_uncertainty_score":0.5186589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00298063952367682,"score_gpt":0.1950349371935187,"score_spread":0.1920542976698418,"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."}}