{"id":"W2156117786","doi":"10.1109/infcomw.2011.5928828","title":"Stochastic unit commitment in smart grid communications","year":2011,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Smart grid; Renewable energy; Computer science; Power system simulation; Grid; Distributed computing; Scheduling (production processes); Demand response; Hidden Markov model; Mathematical optimization; Electric power system; Real-time computing; Power (physics); Electrical engineering; Engineering; Electricity; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001442555,0.0006875651,0.001202068,0.0003776782,0.0005542976,0.001142549,0.001185986,0.001107033,0.003686024],"category_scores_gemma":[0.004629123,0.0005028285,0.0004875496,0.001382416,0.001167913,0.001512718,0.001010206,0.001767813,0.0004997441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001299609,"about_ca_system_score_gemma":0.001194249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004475517,"about_ca_topic_score_gemma":0.004095274,"domain_scores_codex":[0.9983245,0.0008880622,0.00005631024,0.0002142574,0.0003761264,0.000140896],"domain_scores_gemma":[0.9972851,0.001930123,0.0002463365,0.0002011315,0.0002370392,0.0001001717],"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":[0.00004067899,0.00002069003,0.0002066496,0.00004246638,0.00002473919,0.0001076185,0.00004407748,0.8767469,0.0004027442,0.1082289,0.001430261,0.01270435],"study_design_scores_gemma":[0.000005979096,0.000008708491,0.00002760973,0.000003987779,0.000002623871,0.00001332162,0.000007908758,0.9751966,0.0001024057,0.02421466,0.0004119774,0.000004290193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02270319,0.0010491,0.965607,0.001088639,0.000216372,0.00004462811,0.00008443838,0.0001836266,0.00902295],"genre_scores_gemma":[0.9426159,0.001296678,0.04754454,0.0002100254,0.0002286184,0.0001277953,0.0001359678,0.00006596918,0.007774404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004475517,"threshold_uncertainty_score":0.01233095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0623980806473708,"score_gpt":0.2293407170217951,"score_spread":0.1669426363744243,"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."}}