{"id":"W2119196062","doi":"10.1109/pecon.2012.6450334","title":"Analyzing the economic potential for DG CHP systems at the University of Guelph","year":2012,"lang":"en","type":"article","venue":"","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cogeneration; Electricity; Electricity generation; Environmental economics; Economic dispatch; Distributed generation; Cost of electricity by source; Sustainable energy; Biomass (ecology); Energy modeling; Business; Environmental science; Renewable energy; Electric power system; Computer science; Power (physics); Engineering; Economics; Efficient energy use; 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":[0.0005056083,0.000296909,0.0002356035,0.0004283158,0.0007374391,0.0012373,0.0005528239,0.0005301613,0.002938821],"category_scores_gemma":[0.001761188,0.0002681401,0.0004095595,0.0008978607,0.0003990535,0.0008476696,0.0003996881,0.0005240836,0.0001669426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00974997,"about_ca_system_score_gemma":0.003679682,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5426347,"about_ca_topic_score_gemma":0.6530924,"domain_scores_codex":[0.9996848,0.0001067115,0.000005088669,0.00003215852,0.00008505715,0.00008612833],"domain_scores_gemma":[0.9995492,0.0002486894,0.00002807239,0.00002207993,0.0001063887,0.00004548422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001947629,0.00002773076,0.01908225,0.00005975449,0.00003759945,0.0003294438,0.0001019201,0.958798,0.001516432,0.008675265,0.001132968,0.01004381],"study_design_scores_gemma":[0.0000346968,0.0001080891,0.02340794,0.00003021833,0.00003941332,0.00007972636,0.0005283522,0.9657866,0.002581651,0.002532409,0.004840653,0.00003029103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9509383,0.0003335839,0.009969885,0.0008298973,0.00001762424,0.00008117523,0.0008471906,0.00005913367,0.03692325],"genre_scores_gemma":[0.9944377,0.0001379639,0.001666602,0.00001497532,0.000001979458,0.00001317365,0.0001637021,0.000009648585,0.003554115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4573653,"threshold_uncertainty_score":0.9201177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006120102986725776,"score_gpt":0.1697167070165664,"score_spread":0.1635966040298406,"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."}}