{"id":"W1820091595","doi":"10.1002/wene.151","title":"Research with disaggregated electricity end‐use data in households: review and recommendations","year":2014,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Energy and Environment","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Ontario Centres of Excellence","keywords":"Electricity; Context (archaeology); Sustainability; Work (physics); Environmental economics; Resource (disambiguation); Computer science; Risk analysis (engineering); Data science; Business; Engineering; Economics; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01698955,0.001234559,0.004714385,0.009368702,0.0006353811,0.00390893,0.003225639,0.002936789,0.006874171],"category_scores_gemma":[0.05116775,0.001159542,0.005792442,0.01352939,0.001516292,0.006740442,0.002065524,0.003061344,0.001281337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003750636,"about_ca_system_score_gemma":0.01784476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02356085,"about_ca_topic_score_gemma":0.05081803,"domain_scores_codex":[0.9936281,0.002114747,0.002050534,0.0006687167,0.001269143,0.0002688074],"domain_scores_gemma":[0.9416107,0.04275846,0.005354478,0.001199778,0.008456076,0.0006205894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001465495,0.00006761993,0.001753638,0.3997699,0.002034976,0.0002043427,0.0009625237,0.000445243,0.0002493861,0.004963139,0.03504981,0.5543529],"study_design_scores_gemma":[0.0000524418,0.00007098786,0.004844802,0.6337767,0.00472988,0.0003925034,0.001114294,0.0001889089,0.0002117692,0.004424617,0.3501132,0.00008003583],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001341902,0.9960121,0.0002653437,0.002715274,0.0003164576,0.00005155104,0.0002003486,0.000009838745,0.0002950185],"genre_scores_gemma":[0.001414654,0.9960479,0.0009289065,0.00113005,0.0001330096,0.0001118443,0.0001203992,0.000005057855,0.000108073],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02356085,"threshold_uncertainty_score":0.08985043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05393670672655108,"score_gpt":0.2914948454162865,"score_spread":0.2375581386897354,"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."}}