{"id":"W2418133265","doi":"10.1038/sdata.2016.37","title":"Electricity, water, and natural gas consumption of a residential house in Canada from 2012 to 2014","year":2016,"lang":"en","type":"article","venue":"Scientific Data","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":288,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"British Columbia Institute of Technology","keywords":"Electricity; Consumption (sociology); Sustainability; Environmental economics; Power consumption; Computer science; Natural resource; Natural gas; Power (physics); Engineering; Economics; Ecology; Waste management","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":[0.0002102787,0.0004993994,0.0004151559,0.002074168,0.0008915187,0.0008790793,0.0009991765,0.0003660757,0.002602638],"category_scores_gemma":[0.0009343579,0.0002396457,0.0004921842,0.006053785,0.0004005068,0.0004913981,0.0006930656,0.000518646,0.0007486994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01717061,"about_ca_system_score_gemma":0.01027827,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9922137,"about_ca_topic_score_gemma":0.9970693,"domain_scores_codex":[0.9996891,0.000012405,0.00001749352,0.00006382286,0.0001224521,0.00009464242],"domain_scores_gemma":[0.9992064,0.00003193484,0.00005848173,0.00003186912,0.0005674412,0.0001039563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005472995,0.000199387,0.6777259,0.0004750367,0.000336799,0.0004370536,0.0009804938,0.01711399,0.001034638,0.00222765,0.2492104,0.04971139],"study_design_scores_gemma":[0.00002195761,0.00001911398,0.9456213,0.0001297724,0.00005023085,0.0001262481,0.002058835,0.008929452,0.0007061814,0.0002552687,0.0420225,0.00005912412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3894913,0.0006721492,0.0005686363,0.0005007523,0.00003426347,0.00004271232,0.6019522,0.0002955371,0.0064424],"genre_scores_gemma":[0.5136465,0.00075179,0.001467534,0.0001356842,0.00001643574,0.0000395779,0.477462,0.00005967677,0.006420942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01717061,"threshold_uncertainty_score":0.1245821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223721011083671,"score_gpt":0.2024199108008323,"score_spread":0.1901827006899956,"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."}}