{"id":"W2151985588","doi":"10.1109/ann.1991.213464","title":"Joint VAr controller implemented in an artificial neural network environment","year":2002,"lang":"en","type":"article","venue":"","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Hydro (Canada)","funders":"National Research Council Canada","keywords":"Artificial neural network; Joint (building); Computer science; Artificial intelligence; Controller (irrigation); Point (geometry); Control (management); Machine learning; Control engineering; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003580937,0.0004132923,0.0004078061,0.0002309573,0.0002841493,0.0007763277,0.0008430174,0.0006524044,0.004389287],"category_scores_gemma":[0.0006960084,0.0002285389,0.0002435294,0.0002597366,0.0002299851,0.0005747788,0.0004032849,0.0007804392,0.001226121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002912745,"about_ca_system_score_gemma":0.0003777924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003314108,"about_ca_topic_score_gemma":0.004175716,"domain_scores_codex":[0.9997106,0.00005037139,0.00001903419,0.00006128254,0.0001265266,0.00003210114],"domain_scores_gemma":[0.9998052,0.0000523915,0.00001873404,0.00003518708,0.00007798847,0.00001064718],"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":[0.0004900037,0.0002120692,0.000790815,0.0001687449,0.00008038912,0.0002380877,0.0001326624,0.7064987,0.03724156,0.02231208,0.005184539,0.2266503],"study_design_scores_gemma":[0.00002050376,0.00005141478,0.0001164789,0.00000453657,0.000008730519,0.00002688486,0.000004545803,0.9859657,0.008662094,0.001112053,0.004018171,0.000008901033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03083627,0.0001456027,0.9424919,0.000161298,0.0001985252,0.00006488278,0.00008867952,0.008527299,0.01748553],"genre_scores_gemma":[0.7027849,0.0001508282,0.2714267,0.0001324473,0.00005300842,0.0001638793,0.0002162377,0.0002614118,0.02481052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004389287,"threshold_uncertainty_score":0.0146836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03078340073474339,"score_gpt":0.2094042571117764,"score_spread":0.178620856377033,"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."}}