{"id":"W2949152365","doi":"10.3390/su11123264","title":"Exergy and Exergoeconomic Analyses of a Combined Power Producing System including a Proton Exchange Membrane Fuel Cell and an Organic Rankine Cycle","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Exergy; Organic Rankine cycle; Condenser (optics); Exergy efficiency; Proton exchange membrane fuel cell; Process engineering; Gas compressor; Heat exchanger; Waste management; Rankine cycle; Degree Rankine; Engineering; Overall pressure ratio; Turbine; Waste heat; Nuclear engineering; Environmental science; Thermodynamics; Mechanical engineering; Power (physics); Fuel cells; Chemical engineering","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":[0.0005738667,0.0002486834,0.0006038111,0.0001433226,0.00006446829,0.00003857108,0.0001446071,0.0001037312,0.00006220016],"category_scores_gemma":[0.0000319838,0.0002306735,0.0000699446,0.000177895,0.00007206967,0.0002150726,0.00009501656,0.0001202216,0.000002656309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002799448,"about_ca_system_score_gemma":0.00006182553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006302182,"about_ca_topic_score_gemma":0.00003192691,"domain_scores_codex":[0.9985792,0.00008627759,0.0004549614,0.0004343412,0.0001182269,0.0003269674],"domain_scores_gemma":[0.9990527,0.00004669733,0.0001046914,0.0005139,0.0001651575,0.0001168641],"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":[0.002554954,0.001236028,0.1836875,0.3181019,0.001521567,0.0000693149,0.08224627,0.06305196,0.3393884,0.003051589,0.00006723406,0.005023391],"study_design_scores_gemma":[0.01301424,0.0024937,0.08016627,0.001270157,0.0009984615,0.00009603852,0.06983304,0.7582952,0.06417651,0.005226834,0.0006191887,0.003810408],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952233,0.002004432,0.0005691504,0.00001858697,0.0001367408,0.001060271,0.00000706226,0.0001744174,0.0008060548],"genre_scores_gemma":[0.9996206,0.00007211237,0.00004341097,0.000003726537,0.00003210409,0.0000536789,0.000007506347,0.00004068093,0.0001262421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6952432,"threshold_uncertainty_score":0.9406592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006856030790311173,"score_gpt":0.2417364702642155,"score_spread":0.2348804394739043,"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."}}