{"id":"W2159855846","doi":"10.1504/ijex.2006.009780","title":"Application of temperature-distribution models to evaluate the energy and exergy of stratified thermal storages","year":2006,"lang":"en","type":"article","venue":"International Journal of Exergy","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Exergy; Thermal stratification; Thermal energy storage; Stratification (seeds); Thermal; Environmental science; Thermal energy; Energy (signal processing); Computer science; Thermodynamics; Process engineering; Mathematics; Physics; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002034557,0.00009367816,0.0001889542,0.00007955742,0.0000199071,0.00001927846,0.0002527373,0.00004981485,0.000008316492],"category_scores_gemma":[0.000006443551,0.00006671974,0.00008620315,0.0000759046,0.00003438954,0.0001000984,0.00001801221,0.00006005455,3.120501e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003694919,"about_ca_system_score_gemma":0.00002398986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000445775,"about_ca_topic_score_gemma":0.00004520353,"domain_scores_codex":[0.9990185,0.00002813331,0.0004672602,0.00006660356,0.0003384879,0.00008096779],"domain_scores_gemma":[0.999299,0.00003955187,0.000153239,0.00009644698,0.000379886,0.00003187485],"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":[0.000111571,0.00004456625,0.00006924476,0.00001276424,0.0001971577,0.000002598843,0.0001887827,0.7640429,0.1977208,0.03155855,0.0006937088,0.005357377],"study_design_scores_gemma":[0.001988406,0.000334643,0.01005859,0.0004004147,0.0002494871,0.0001658212,0.00107588,0.8209903,0.1415407,0.01794603,0.00471936,0.0005303499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.758358,0.001245853,0.2390356,0.0001245074,0.0004043933,0.00004354093,0.0000389757,0.00001079038,0.0007383233],"genre_scores_gemma":[0.9995056,0.00008665704,0.00009211191,0.00001432733,0.0002124602,0.000003868791,0.00001981567,0.000009685742,0.00005540895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2411477,"threshold_uncertainty_score":0.2720752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00622971963488216,"score_gpt":0.2244598731573399,"score_spread":0.2182301535224577,"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."}}