{"id":"W1989255300","doi":"10.1145/2487166.2487205","title":"Efficient demand assignment in multi-connected microgrids","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Distributed computing; Grid; Distributed generation; Generator (circuit theory); Set (abstract data type); Microgrid; Resource (disambiguation); Distributed power generation; Duration (music); On demand; Demand response; Electricity generation; Power (physics); Computer network; Engineering; Renewable energy; Electrical engineering; Control (management); Electricity; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003464437,0.00009596923,0.00009205696,0.00006106329,0.00001505852,0.00001686905,0.00005302391,0.00004772253,0.0002326806],"category_scores_gemma":[0.000006692715,0.00009028114,0.00001481032,0.0001718674,0.000009946313,0.00004231985,0.00001532047,0.00007025085,0.0001309441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008749127,"about_ca_system_score_gemma":0.000002651396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001386119,"about_ca_topic_score_gemma":0.00001978559,"domain_scores_codex":[0.9994578,0.00001068784,0.0001577731,0.0001101514,0.00005956353,0.0002040044],"domain_scores_gemma":[0.9997948,0.00002660261,0.00001107446,0.0001067108,0.00001808717,0.00004275804],"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":[6.103012e-7,0.00002975627,0.0006238812,0.000006419968,0.000004306483,9.022047e-7,0.00005812732,0.9896505,0.006833876,0.00002762538,0.0003198622,0.002444084],"study_design_scores_gemma":[0.0004197778,0.000005469797,0.004508225,0.00001342187,0.000001363362,7.245173e-7,0.00003351002,0.9898216,0.00496395,0.00001041439,0.0001036194,0.0001179019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2951383,0.0001524708,0.7033348,0.00002182741,0.0001053579,0.000248944,4.08031e-7,0.0002466723,0.0007512223],"genre_scores_gemma":[0.959729,0.00002465087,0.04001314,0.00002979754,0.00001561582,0.00006246651,0.000005707511,0.00002218489,0.00009750219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6645907,"threshold_uncertainty_score":0.3681558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007163071033707756,"score_gpt":0.1988019290989845,"score_spread":0.1916388580652767,"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."}}