{"id":"W4407720590","doi":"10.1002/est2.70145","title":"Performance Optimization of Double U‐Tube Borehole Heat Exchanger for Thermal Energy Storage","year":2025,"lang":"en","type":"article","venue":"Energy Storage","topic":"Geothermal Energy Systems and Applications","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Heat exchanger; Tube (container); Borehole; Thermal energy storage; Petroleum engineering; Shell and tube heat exchanger; Thermal; Nuclear engineering; Environmental science; Materials science; Mechanical engineering; Geology; Thermodynamics; Engineering; Geotechnical engineering; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001881497,0.0003143211,0.0004211807,0.0002513602,0.0002654445,0.00003792793,0.0003884587,0.0002263872,0.0002943307],"category_scores_gemma":[0.000009564008,0.0003005843,0.0001909147,0.0005380167,0.00009085558,0.0002214856,0.00009075846,0.00008176409,0.000005125912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081877,"about_ca_system_score_gemma":0.00009869226,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008614141,"about_ca_topic_score_gemma":0.0005565215,"domain_scores_codex":[0.9982811,0.00006264517,0.000521852,0.0004647268,0.0002331389,0.0004366008],"domain_scores_gemma":[0.9987732,0.00007368645,0.0001641738,0.0006911404,0.0002009005,0.0000968656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001116061,0.0001123071,0.00004319977,0.00005685407,0.0000747443,0.000001013713,0.00008865407,0.8211038,0.006093462,0.1669216,0.001182969,0.004209801],"study_design_scores_gemma":[0.001782018,0.0001047398,0.0003483157,0.00008545862,0.00005371014,0.000002118528,0.00007525671,0.4625432,0.02732548,0.0001260124,0.5071764,0.000377268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2906704,0.003180769,0.3991453,0.00108044,0.002138204,0.0006229741,0.0001308541,0.000617125,0.302414],"genre_scores_gemma":[0.9619669,0.000106483,0.001444399,0.00037214,0.000324545,0.0006649277,0.000212452,0.00007055316,0.03483754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6712966,"threshold_uncertainty_score":0.9999446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218609608166588,"score_gpt":0.2263139784717003,"score_spread":0.2141278823900344,"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."}}