{"id":"W1963767778","doi":"10.1504/ijex.2014.066610","title":"Exergy analysis of a multi-tank thermal storage system for solar heating applications","year":2014,"lang":"en","type":"article","venue":"International Journal of Exergy","topic":"Solar Thermal and Photovoltaic Systems","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TRNSYS; Exergy; Environmental science; Nuclear engineering; Volume (thermodynamics); Work (physics); Mechanics; Exergy efficiency; Charge (physics); Materials science; Constant (computer programming); Thermodynamics; Thermal; Computer science; Physics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002011359,0.0002700275,0.0005121839,0.0002937308,0.0003440091,0.0003305826,0.0003316376,0.0001697417,0.00206426],"category_scores_gemma":[0.0002354604,0.0001251906,0.00034937,0.0003027476,0.0001880585,0.0005461677,0.0002594982,0.0001840202,0.0002385078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004474474,"about_ca_system_score_gemma":0.0004342922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001782156,"about_ca_topic_score_gemma":0.002654862,"domain_scores_codex":[0.9999293,0.00001030122,0.000007044561,0.00001173648,0.00002963982,0.00001188623],"domain_scores_gemma":[0.9999193,0.00003119775,0.000008464271,0.000008057945,0.00002313997,0.000009834141],"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":[0.001467022,0.0001984351,0.005463231,0.0003441436,0.00004719484,0.0001819994,0.0001406318,0.06133929,0.9045684,0.0002963889,0.0001674021,0.02578585],"study_design_scores_gemma":[0.00007618136,0.001954331,0.02925175,0.00002003158,0.00009309178,0.0001344675,0.000242199,0.1898395,0.7764911,0.0004583077,0.001400593,0.00003840589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930809,0.0001280631,0.005863939,0.00001829542,0.000005802167,0.0000351225,0.0002258577,0.00004978393,0.000592138],"genre_scores_gemma":[0.9983222,0.00004994803,0.0009584951,0.000002849036,8.981355e-7,0.0000160889,0.0001015145,0.000006263599,0.0005417184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00206426,"threshold_uncertainty_score":0.006905615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01810169371068766,"score_gpt":0.2740508814499731,"score_spread":0.2559491877392855,"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."}}