{"id":"W4382491853","doi":"10.1080/19942060.2023.2208196","title":"Photovoltaic-thermal system combined with wavy tubes, twisted tape inserts and a novel coolant fluid: energy and exergy analysis","year":2023,"lang":"en","type":"article","venue":"Engineering Applications of Computational Fluid Mechanics","topic":"Solar Thermal and Photovoltaic Systems","field":"Energy","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Engineering and Physical Sciences Research Council; University of Manchester","keywords":"Exergy; Photovoltaic system; Coolant; Exergy efficiency; Materials science; Thermal; Thermal energy; Nuclear engineering; Parametric statistics; Working fluid; Mechanical engineering; Environmental science; Process engineering; Engineering; Electrical engineering; Thermodynamics; Physics; Mathematics","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":[0.0002302374,0.0002723261,0.0004656779,0.0005330562,0.0001272121,0.00004385084,0.0001788329,0.0001164004,0.000008468897],"category_scores_gemma":[0.00001796407,0.0002608137,0.00007825563,0.001790372,0.0000274286,0.0000785104,0.00008262561,0.00007680833,0.000005438153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005414561,"about_ca_system_score_gemma":0.00004897073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009986978,"about_ca_topic_score_gemma":0.00005774038,"domain_scores_codex":[0.9984801,0.00003006772,0.0004728589,0.0003953374,0.0003622222,0.000259435],"domain_scores_gemma":[0.9988961,0.0002863297,0.000119873,0.0003222632,0.0002211042,0.0001543743],"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":[0.00006848354,0.00004983659,0.00006021315,0.0001649973,0.0006220163,0.000003642127,0.0001478882,0.6615739,0.2014971,0.1353029,0.00002395174,0.0004850794],"study_design_scores_gemma":[0.0008108859,0.00009585793,0.001115535,0.00006970433,0.0002283106,0.00003490649,0.0001408234,0.9841383,0.01070137,0.0002353458,0.002139412,0.0002895757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.494488,0.0002815451,0.5042177,0.00001762059,0.00006717212,0.0003235947,0.0001028904,0.0004237748,0.00007770236],"genre_scores_gemma":[0.9954869,0.000022046,0.003392962,0.00002471333,0.00005670466,0.0003991307,0.0004859993,0.00005596779,0.00007558782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5009989,"threshold_uncertainty_score":0.9999844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006393244362498416,"score_gpt":0.1864255670029725,"score_spread":0.1800323226404741,"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."}}