{"id":"W2564509497","doi":"10.1504/ijex.2016.076863","title":"Exergy assessment of heat transfer inside a Beta type Stirling engine","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Thermodynamic Systems and Engines","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Stirling engine; Exergy; Heat transfer; Nuclear engineering; Pressure drop; Thermodynamics; Mechanical engineering; Exergy efficiency; Environmental science; Thermal; Mechanics; Materials science; Engineering; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001249936,0.0003351457,0.000499872,0.0001739186,0.00006822848,0.00005341216,0.0005658047,0.0002442463,0.00007982326],"category_scores_gemma":[0.00009992717,0.0003147221,0.0001619555,0.0002068248,0.00007561007,0.00009243251,0.000237493,0.0003802797,0.000007053454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001475646,"about_ca_system_score_gemma":0.0001030496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002007561,"about_ca_topic_score_gemma":0.0002478068,"domain_scores_codex":[0.997893,0.0005969346,0.0005527158,0.0003889723,0.0002734677,0.0002949373],"domain_scores_gemma":[0.9972789,0.000480956,0.00005554653,0.001296596,0.0007745271,0.000113529],"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":[0.0000281668,0.0005807808,0.001852798,0.004004404,0.001135142,0.00001906478,0.009860058,0.3716035,0.3243375,0.1667639,0.0004428189,0.1193719],"study_design_scores_gemma":[0.001396015,0.000001390719,0.005045745,0.01149681,0.0001415077,0.00001753144,0.0001255458,0.8299981,0.132053,0.004670942,0.01361139,0.001442041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1605545,0.002048722,0.8078881,0.0004284968,0.0006185538,0.000311241,0.00008383248,0.0003920011,0.02767457],"genre_scores_gemma":[0.9818147,0.001074628,0.0159514,0.000006548415,0.00004096634,0.00004550114,0.0001444567,0.00009011533,0.0008316335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8212603,"threshold_uncertainty_score":0.9999305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089724678248272,"score_gpt":0.2259007755875913,"score_spread":0.2150035288051086,"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."}}