{"id":"W2617709255","doi":"10.15173/esr.v9i1.406","title":"Energy Use in the Commercial Sector: Estimated Intensities and Costs for Canada Based on US Survey Data","year":2000,"lang":"en","type":"article","venue":"Energy Studies Review","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Resources Canada; McMaster University","keywords":"Energy (signal processing); Survey data collection; Energy sector; Environmental economics; Environmental science; Natural resource economics; Agricultural economics; Business; Econometrics; Economics; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0009159554,0.0003649799,0.0003789038,0.004010167,0.0007857648,0.00136107,0.0007901886,0.0001881868,0.001664961],"category_scores_gemma":[0.003732842,0.0002302864,0.0007826918,0.01368408,0.0003255392,0.0005585789,0.0005169912,0.0003747594,0.0002587042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02702264,"about_ca_system_score_gemma":0.02274429,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944504,"about_ca_topic_score_gemma":0.9954566,"domain_scores_codex":[0.9989237,0.0001116627,0.00008385892,0.0001015601,0.0006384727,0.0001407138],"domain_scores_gemma":[0.9973447,0.0003049287,0.0002979094,0.00008643694,0.001852442,0.0001135631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001354709,0.00005500956,0.9416151,0.0003877724,0.0003353222,0.00009206958,0.0006214033,0.01281917,0.0003166914,0.002857102,0.004292249,0.03647264],"study_design_scores_gemma":[0.00001302095,0.00002290251,0.9727839,0.00008321381,0.0001646754,0.00007714302,0.001410748,0.01358537,0.0006689623,0.0003737538,0.01078207,0.00003437871],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9223555,0.004573641,0.003247157,0.0004312122,0.00001217288,0.0001542541,0.05165096,0.00008902077,0.01748607],"genre_scores_gemma":[0.9672208,0.004214054,0.003309538,0.00005050655,0.000004821711,0.00007718329,0.02132287,0.00002678365,0.003773447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02702264,"threshold_uncertainty_score":0.1960639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1210382719743729,"score_gpt":0.3148430788474114,"score_spread":0.1938048068730385,"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."}}