{"id":"W2972517269","doi":"10.1016/j.procs.2019.08.075","title":"Thermodynamic analysis of the performance of sub-critical organic Rankine cycle with borehole thermal energy storage","year":2019,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Organic Rankine cycle; Environmental science; Degree Rankine; Thermal energy storage; Fossil fuel; Borehole; Rankine cycle; Electricity; Process engineering; Greenhouse gas; Thermal efficiency; Nuclear engineering; Waste management; Waste heat; Thermodynamics; Mechanical engineering; Geology; Heat exchanger; Chemistry; Engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001660682,0.0002368928,0.0003480514,0.0002935869,0.0003574671,0.0003147229,0.0003604697,0.0001586087,0.001615161],"category_scores_gemma":[0.0002338396,0.00008307234,0.0002013041,0.0003546087,0.0003594209,0.0003148108,0.0001617329,0.00016561,0.0001256737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000684642,"about_ca_system_score_gemma":0.0004736269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01406674,"about_ca_topic_score_gemma":0.0210623,"domain_scores_codex":[0.9998901,0.000009448741,0.00000522038,0.00001594537,0.00004820459,0.00003111343],"domain_scores_gemma":[0.9999104,0.00002371455,0.000008460652,0.000006062839,0.00003905732,0.00001225173],"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":[0.00357956,0.0005739704,0.0372053,0.0007677744,0.000126218,0.0006519469,0.0003044516,0.1491621,0.7638423,0.002049698,0.001182033,0.04055468],"study_design_scores_gemma":[0.00009716612,0.002083418,0.07698203,0.00001418431,0.00009199187,0.000179917,0.0004872755,0.2656165,0.6513417,0.0004785891,0.002572634,0.00005454321],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998621,0.00008075833,0.0003513359,0.000009310269,0.000003275288,0.000007741114,0.0001105887,0.00001613305,0.0007998472],"genre_scores_gemma":[0.9996345,0.000023565,0.00009074308,0.000001126115,4.632096e-7,0.000001974299,0.00004868257,0.000002161773,0.0001966904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01406674,"threshold_uncertainty_score":0.02796972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002146346474994823,"score_gpt":0.1733508205585748,"score_spread":0.17120447408358,"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."}}