{"id":"W2042926483","doi":"10.1016/j.buildenv.2009.01.011","title":"Convective heat transfer prediction in large rectangular cross-sectional area Earth-to-Air Heat Exchangers","year":2009,"lang":"en","type":"article","venue":"Building and Environment","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Nusselt number; Duct (anatomy); Airflow; Heat exchanger; Computational fluid dynamics; Latin hypercube sampling; Turbulence; Convective heat transfer; Heat transfer; CFD in buildings; Meteorology; Environmental science; Mechanics; Simulation; Engineering; Mechanical engineering; Mathematics; Geography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004944922,0.0005059846,0.0007518739,0.0003257009,0.0005483321,0.0005479669,0.0005700179,0.0005949346,0.0007888772],"category_scores_gemma":[0.0008062872,0.0004209595,0.0005215179,0.0003485969,0.000783544,0.0006055962,0.0003645346,0.0004424464,0.0001210537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005639048,"about_ca_system_score_gemma":0.0005501696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01327994,"about_ca_topic_score_gemma":0.007345559,"domain_scores_codex":[0.9998991,0.00002524086,0.000005490593,0.0000291257,0.00001404355,0.00002690175],"domain_scores_gemma":[0.9991993,0.0005759516,0.00005014122,0.0000451837,0.00007844913,0.0000509558],"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":[0.0001790976,0.00009807805,0.004717332,0.00002594006,0.00001654867,0.00006107217,0.00005198772,0.9788781,0.01227336,0.0003162036,0.00009227112,0.003289798],"study_design_scores_gemma":[0.000009515154,0.000052273,0.00199972,8.557745e-7,0.000004544786,0.000004475692,0.0000155019,0.9952062,0.00264392,0.00003622796,0.00002341303,0.000003341264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893062,0.00005950194,0.009953081,0.00002090213,0.000008557529,0.000008480025,0.00002909042,0.00006337611,0.000550701],"genre_scores_gemma":[0.9986914,0.0000210614,0.0009491385,0.000002049613,0.000002384628,0.000006122254,0.00002042081,0.000006129784,0.0003013337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01327994,"threshold_uncertainty_score":0.02640527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105649358605322,"score_gpt":0.2198418290827123,"score_spread":0.2092768932221801,"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."}}