{"id":"W2337023043","doi":"10.1115/1.4033424","title":"Assessing Cogeneration Activity in Extraction–Condensing Steam Turbines: Dissolving the Issues by Applied Thermodynamics","year":2016,"lang":"en","type":"article","venue":"Journal of Energy Resources Technology","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Cogeneration; Power station; Steam turbine; Thermal power station; Process engineering; Production (economics); Engineering; Electricity generation; Power (physics); Waste management; Mechanical engineering; Thermodynamics; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002943643,0.0001675916,0.0003148826,0.0002868627,0.00009704901,0.00006513263,0.0002828519,0.0002143194,0.00001021723],"category_scores_gemma":[0.00003416324,0.00009747257,0.00008172342,0.000269507,0.000102275,0.0002330343,0.00002842902,0.0002504973,0.00000120172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001314981,"about_ca_system_score_gemma":0.00001619925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003134887,"about_ca_topic_score_gemma":0.00006637552,"domain_scores_codex":[0.9989823,0.0000481544,0.0004259732,0.0001264416,0.0001795052,0.0002376379],"domain_scores_gemma":[0.9993464,0.0001112235,0.0002465878,0.0002011958,0.00006026671,0.00003436322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003193613,0.00003620855,0.0004465847,0.00001064685,0.0001141844,0.00001030352,0.000175972,0.008616454,0.8579451,0.001043296,0.0001848371,0.1313845],"study_design_scores_gemma":[0.007292617,0.0007054828,0.00856784,0.002896039,0.0007055123,0.002094449,0.023603,0.3689701,0.3647258,0.02467407,0.1921314,0.00363367],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8645926,0.002367521,0.1311277,0.0005152845,0.0002661811,0.00002856333,0.000001218552,0.00008480211,0.001016163],"genre_scores_gemma":[0.9990711,0.0004057612,0.0001439471,0.00001563273,0.0001720906,0.000003824531,6.629447e-7,0.00002949275,0.0001575382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4932193,"threshold_uncertainty_score":0.3974816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005839967628340736,"score_gpt":0.2351243783844624,"score_spread":0.2292844107561217,"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."}}