{"id":"W2026045102","doi":"10.1115/es2012-91148","title":"Modeling of Gas Turbine-Based Cogeneration System","year":2012,"lang":"en","type":"article","venue":"","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cogeneration; Combined cycle; Thermal efficiency; Superheated steam; Steam turbine; Process engineering; Steam-electric power station; Electricity; Thermal power station; Power station; Environmental science; Turbine; Work (physics); Electricity generation; Automotive engineering; Thermal energy; Engineering; Waste management; Power (physics); Mechanical engineering; Electrical engineering; Chemistry; Thermodynamics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0002141259,0.0009766165,0.001099668,0.0004575682,0.0009090378,0.00147433,0.001767017,0.002200785,0.006867292],"category_scores_gemma":[0.0004348821,0.0005642785,0.0009066646,0.0005506024,0.0006694187,0.001090073,0.0007555111,0.0008863114,0.001440025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001085588,"about_ca_system_score_gemma":0.001376963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02812721,"about_ca_topic_score_gemma":0.01052143,"domain_scores_codex":[0.9998011,0.00004454778,0.00001123982,0.00004904735,0.0000596952,0.00003440226],"domain_scores_gemma":[0.9998603,0.00004786185,0.00001979169,0.00001206404,0.0000462393,0.00001368378],"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":[0.00001674901,0.00001175076,0.0002067274,0.0000322709,0.000008392938,0.00008289872,0.00002747638,0.9952812,0.001058621,0.001931322,0.0002141311,0.001128397],"study_design_scores_gemma":[0.00001029407,0.00001392183,0.0001515479,0.000004752283,0.000004894877,0.00001619268,0.00001013406,0.998009,0.0002599598,0.0005451934,0.0009689467,0.000005154301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2712079,0.001677444,0.5440719,0.0009111461,0.0003745891,0.0005430451,0.00392062,0.003094897,0.1741984],"genre_scores_gemma":[0.9522248,0.0006735841,0.01317941,0.00009479769,0.00003752632,0.0004645337,0.0009323711,0.0001795708,0.03221337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02812721,"threshold_uncertainty_score":0.05592704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026448199089602,"score_gpt":0.2027274085470838,"score_spread":0.1924629265561878,"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."}}