{"id":"W4244250304","doi":"10.32920/ryerson.14663082","title":"Estimating power consumption in City of Toronto: a case study","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Electricity; Electricity demand; Electricity generation; Renewable energy; Consumption (sociology); Environmental economics; Peak demand; Electricity retailing; Energy demand; Business; Economics; Power (physics); Electricity market; Engineering; Electrical 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":[0.0003645626,0.0004574022,0.0002365556,0.001402345,0.001137141,0.000966792,0.0007040033,0.0007042526,0.001868122],"category_scores_gemma":[0.001802091,0.0002109468,0.000491159,0.006272859,0.0005464421,0.0003743211,0.000463366,0.0003297281,0.0001882318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01146362,"about_ca_system_score_gemma":0.002849593,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9493018,"about_ca_topic_score_gemma":0.9660887,"domain_scores_codex":[0.9996194,0.00008225733,0.00002660164,0.00005630268,0.0001120401,0.0001034553],"domain_scores_gemma":[0.998808,0.0005667275,0.0001121472,0.00007854146,0.0003345991,0.0001000157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003942761,0.0003058281,0.6609799,0.0006619294,0.0003281598,0.01453953,0.007124995,0.2436735,0.003761902,0.00542933,0.01363664,0.04916399],"study_design_scores_gemma":[0.00003330818,0.0001197129,0.7600015,0.0001152531,0.0001524228,0.0008742537,0.02448999,0.1975894,0.001902386,0.0007095777,0.01391537,0.00009679881],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878706,0.0003491623,0.001558903,0.0003454197,0.000008757293,0.00006059881,0.004403564,0.00005230489,0.005350665],"genre_scores_gemma":[0.9928945,0.0004382919,0.001578412,0.00002053217,0.000007508198,0.00001730797,0.002976883,0.0000124647,0.002054123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05069816,"threshold_uncertainty_score":0.1019934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03022307324850706,"score_gpt":0.2822693014475525,"score_spread":0.2520462281990454,"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."}}