{"id":"W4251619464","doi":"10.32920/ryerson.14649009","title":"Analysis of natural gas consumption and energy saving measures for powder coating and food processing companies in the Greater Toronto Area (GTA)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Energy consumption; Energy intensity; Natural gas; Environmental science; Efficient energy use; Energy balance; Consumption (sociology); Waste management; Process engineering; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001130933,0.0001684544,0.00008250047,0.0008053696,0.0002486802,0.0002850512,0.0002091545,0.0001229285,0.001561768],"category_scores_gemma":[0.0003284186,0.00008611941,0.0002019844,0.001551606,0.0001374453,0.0001951504,0.0001897746,0.00009498026,0.0001533249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003382294,"about_ca_system_score_gemma":0.001015532,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.536507,"about_ca_topic_score_gemma":0.7672478,"domain_scores_codex":[0.9998755,0.00001602763,0.000005504761,0.00002269501,0.0000440742,0.00003615787],"domain_scores_gemma":[0.999754,0.00004868676,0.0000619446,0.00001021209,0.00008877776,0.00003632573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005062072,0.00009559349,0.9520203,0.0001827895,0.00008129403,0.0004110066,0.00159628,0.006984901,0.01308047,0.0003935815,0.00151968,0.02312799],"study_design_scores_gemma":[0.000001666598,0.00004391798,0.9963971,0.000003559095,0.000007816748,0.00002491658,0.0009020025,0.00106882,0.0009945766,0.000007884881,0.0005444835,0.000003322292],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977105,0.00004529296,0.00009145651,0.00001341536,4.338021e-7,0.000007146581,0.001271797,0.000005341669,0.0008545441],"genre_scores_gemma":[0.9966954,0.00005366486,0.0001555211,0.000003104766,5.973607e-7,0.000005666325,0.001320541,0.00000212087,0.001763484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.463493,"threshold_uncertainty_score":0.9324453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03746698659533035,"score_gpt":0.265664556115618,"score_spread":0.2281975695202877,"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."}}