{"id":"W3179136270","doi":"10.1016/j.enbuild.2021.111280","title":"The impact of the COVID-19 on households’ hourly electricity consumption in Canada","year":2021,"lang":"en","type":"article","venue":"Energy and Buildings","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":83,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electricity; Consumption (sociology); Coronavirus disease 2019 (COVID-19); Mains electricity; Pandemic; Subsidy; Descriptive statistics; Agricultural economics; Economics; Geography; Statistics; Mathematics; Engineering; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0006425802,0.0002405676,0.0003484307,0.0007239187,0.001725756,0.002130228,0.001102589,0.0005617346,0.004242979],"category_scores_gemma":[0.002322662,0.0002699292,0.0006656059,0.002238468,0.0005675417,0.0004186071,0.001329979,0.001110442,0.0002733863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05460777,"about_ca_system_score_gemma":0.04242137,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.998045,"about_ca_topic_score_gemma":0.9987533,"domain_scores_codex":[0.998657,0.00008807016,0.00004076292,0.00007312393,0.0006109113,0.0005301553],"domain_scores_gemma":[0.9974126,0.0001626329,0.0001629731,0.00004719744,0.001620524,0.0005940662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004998418,0.0001893354,0.9078336,0.0001533376,0.0002261092,0.0004471201,0.001123871,0.01323777,0.0006890344,0.00770619,0.04401281,0.02388097],"study_design_scores_gemma":[0.00001513293,0.00002259333,0.9745935,0.00004771936,0.00003314404,0.00002724971,0.002149742,0.004139675,0.0002679315,0.000151759,0.01852885,0.00002271171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9193926,0.0012168,0.0004705267,0.005537718,0.0001444678,0.00006190417,0.03460337,0.00006564714,0.0385069],"genre_scores_gemma":[0.9829776,0.0005651185,0.0002278164,0.0003311685,0.00001642022,0.0000144943,0.005549105,0.00002385653,0.0102944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05460777,"threshold_uncertainty_score":0.3962089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367508410050249,"score_gpt":0.2804556713874869,"score_spread":0.2567805872869844,"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."}}