{"id":"W1998871774","doi":"10.1007/s11630-012-0518-5","title":"Direct numerical simulation of convective heat transfer in a zero-pressure- gradient boundary layer with supercritical water","year":2012,"lang":"en","type":"article","venue":"Journal of Thermal Science","topic":"Heat transfer and supercritical fluids","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Atomic Energy of Canada Limited; Government of Ontario","keywords":"Boundary layer; Convective heat transfer; Materials science; Heat transfer; Supercritical fluid; Churchill–Bernstein equation; Heat flux; Mechanics; Thermodynamics; Turbulence; Pressure gradient; Film temperature; Convection; Heat transfer coefficient; Temperature gradient; Mass flux; Reynolds number; Nusselt number; Physics; Meteorology","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":[0.0007011312,0.0001132477,0.0002719773,0.0001305768,0.00004785772,0.0000258555,0.0001755622,0.00004816115,0.0001065087],"category_scores_gemma":[0.00003299974,0.00006748569,0.00007201663,0.0002393815,0.0003150797,0.0008359611,0.00000935666,0.0002356029,0.000003477699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006795163,"about_ca_system_score_gemma":0.00003996481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001920444,"about_ca_topic_score_gemma":0.000002103117,"domain_scores_codex":[0.9985901,0.00005651834,0.0003287396,0.00009145818,0.0004739937,0.0004591967],"domain_scores_gemma":[0.9994346,0.0001091145,2.804987e-7,0.0000861471,0.0001215208,0.0002483635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001152665,0.0001462803,0.009963182,0.00003932899,0.00002316778,0.00001179861,0.003359487,0.03993383,0.945937,0.0003044106,0.000002555664,0.000163741],"study_design_scores_gemma":[0.0007574381,0.0003957778,0.06895643,0.00008499938,0.00005747228,0.00007736602,0.0001238655,0.02836842,0.9007238,0.00003146336,0.0002185659,0.000204475],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9657218,0.0002494124,0.03226539,0.00008734211,0.0001972097,0.00007126798,0.000002840691,0.00001177407,0.001392967],"genre_scores_gemma":[0.9997818,0.000006170089,0.00009077099,0.00004528069,0.00006155325,0.00000158101,1.731175e-7,0.00001183852,8.687357e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05899325,"threshold_uncertainty_score":0.2751987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01391934502293462,"score_gpt":0.2496292940288881,"score_spread":0.2357099490059535,"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."}}