{"id":"W2163645342","doi":"10.1145/2018536.2018544","title":"Markovian models for home electricity consumption","year":2011,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Representativeness heuristic; Markov process; Electricity; Computer science; Sizing; Energy consumption; Transformer; Consumption (sociology); Electricity demand; Markov chain; Econometrics; Mathematical optimization; Reliability engineering; Operations research; Electricity generation; Statistics; Machine learning; Engineering; Mathematics; Voltage; Electrical engineering","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":[0.00006470598,0.00007520683,0.00006842803,0.00006558242,0.00001981567,0.000007846756,0.00007560285,0.00003199756,0.0002022271],"category_scores_gemma":[0.000002050908,0.00007485406,0.00003149578,0.00005368735,0.000006406853,0.0001116529,0.00001249474,0.00002972654,0.0000460573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004039197,"about_ca_system_score_gemma":0.000001830481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002026656,"about_ca_topic_score_gemma":0.00002371633,"domain_scores_codex":[0.9995909,0.000003605021,0.00008971585,0.00009105432,0.0000507017,0.0001740192],"domain_scores_gemma":[0.9998019,0.00001199516,0.00000681803,0.0001313156,0.0000128774,0.0000351492],"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":[0.0000816168,0.0001166381,0.004001829,0.0003736638,0.0003562631,0.000006074513,0.000432486,0.5724078,0.001744784,0.3216172,0.07535722,0.02350441],"study_design_scores_gemma":[0.0002838193,0.0000267393,0.005377582,0.000003281248,0.00001672798,8.802665e-7,0.000006025831,0.9789854,0.005152421,0.0066898,0.003276552,0.0001808243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06316575,0.00005476628,0.8538472,0.000008473891,0.0003418183,0.0001769079,0.00000206499,0.0005803682,0.08182263],"genre_scores_gemma":[0.9873177,0.00005208806,0.01166585,0.0000514674,0.00004714349,0.00006786844,0.000005291262,0.00002218496,0.0007704513],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9241519,"threshold_uncertainty_score":0.305246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04197466360932862,"score_gpt":0.1975379599165258,"score_spread":0.1555632963071972,"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."}}