{"id":"W2172966071","doi":"10.3390/app5041134","title":"An Efficient Power Scheduling Scheme for Residential Load Management in Smart Homes","year":2015,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Dalhousie University","funders":"King Saud University","keywords":"Knapsack problem; Mathematical optimization; Regret; Maximization; Computer science; Electricity; Scheduling (production processes); Scheme (mathematics); Convergence (economics); Engineering; Mathematics; Electrical engineering; Economics","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":[0.001149428,0.0001558944,0.0001408287,0.0002427143,0.0000966426,0.0001366928,0.0004621988,0.00004077481,0.00001460012],"category_scores_gemma":[0.00001205897,0.0001517369,0.00002960983,0.0005430671,0.0001047625,0.0001320854,0.00009169428,0.00006483066,0.0000472047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001659007,"about_ca_system_score_gemma":0.00003376872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002150134,"about_ca_topic_score_gemma":0.00006145846,"domain_scores_codex":[0.9984148,0.000009770407,0.0002295617,0.0003746302,0.0005282732,0.0004429543],"domain_scores_gemma":[0.999549,0.00002420393,0.00002636582,0.0002587256,0.00002685056,0.0001148584],"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":[0.00001380987,0.00003933836,0.0003065542,0.0000226558,0.00001685997,0.000003852538,0.0003544902,0.9709588,0.0009591932,0.02563409,0.0009749617,0.000715352],"study_design_scores_gemma":[0.002305257,0.0001524075,0.005882022,0.00004884234,0.00002765918,0.00000170415,0.005778854,0.9559415,0.007414463,0.002952724,0.01866927,0.0008253296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9019492,0.000184496,0.03949027,0.0000934569,0.001139865,0.0005484034,0.000001392183,0.0003119571,0.05628096],"genre_scores_gemma":[0.9615598,0.000006343499,0.03806872,0.00005705016,0.00007635669,0.0001589918,0.000002859297,0.00001811806,0.00005178954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05961058,"threshold_uncertainty_score":0.6187651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198468052039694,"score_gpt":0.2531211277162739,"score_spread":0.2332743225123045,"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."}}