{"id":"W2537715746","doi":"10.1109/epc.2007.4520300","title":"Supervisory Hybrid Control of a Micro Grid System","year":2007,"lang":"en","type":"article","venue":"","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Supervisory control; Computer science; Grid; Control (management); Control system; Engineering; Artificial intelligence; Electrical engineering; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002981301,0.000316073,0.000357126,0.0001598819,0.0002772107,0.0006615887,0.0004774352,0.0002651142,0.002004993],"category_scores_gemma":[0.0004070282,0.0001263898,0.0002728395,0.0001413925,0.0006884267,0.0003654956,0.0004942764,0.0005306427,0.0002003341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000320345,"about_ca_system_score_gemma":0.0005137819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00167233,"about_ca_topic_score_gemma":0.001855807,"domain_scores_codex":[0.9997839,0.00004206997,0.00001116608,0.0000578658,0.0000815746,0.00002342366],"domain_scores_gemma":[0.9997694,0.00009217115,0.00004531809,0.00002809879,0.00005197494,0.0000131464],"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":[0.0001549747,0.00005697659,0.0006005723,0.0002114052,0.00006309808,0.0002561242,0.00023546,0.8135457,0.03112989,0.06881855,0.00133626,0.08359098],"study_design_scores_gemma":[0.00002059113,0.0001287132,0.0002051165,0.000009728861,0.00001287999,0.00003698974,0.00002122741,0.9864553,0.002877776,0.007755057,0.002468167,0.0000085003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02119547,0.0001907008,0.9717814,0.0001064292,0.00006210332,0.0000397432,0.00002562465,0.0003679271,0.006230609],"genre_scores_gemma":[0.9567961,0.0002282366,0.0391576,0.00004649365,0.00004888793,0.0001238883,0.00002943721,0.00001896923,0.003550402],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002004993,"threshold_uncertainty_score":0.006707311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00467527304023914,"score_gpt":0.1583711899325755,"score_spread":0.1536959168923364,"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."}}