{"id":"W2071580039","doi":"10.4271/2014-01-1181","title":"Heat and Mass Flow Characterization of Highly Viscous Fluid in Narrow-Channel Heat Exchanger","year":2014,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Heat Transfer and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; University of Windsor","keywords":"Heat exchanger; Mechanics; Flow (mathematics); Materials science; Characterization (materials science); Channel (broadcasting); Micro heat exchanger; Open-channel flow; Fluid dynamics; Petroleum engineering; Thermodynamics; Plate heat exchanger; Computer science; Geology; Physics; Telecommunications; Nanotechnology","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":[0.000313696,0.000176073,0.0001760068,0.0006079678,0.0002471266,0.0002303696,0.0001719184,0.0002287794,0.0007983186],"category_scores_gemma":[0.0003577573,0.0001042553,0.000174822,0.0002970319,0.000324123,0.0003541994,0.0001226906,0.0001546884,0.00009572131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002066251,"about_ca_system_score_gemma":0.0001339189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001059542,"about_ca_topic_score_gemma":0.001005096,"domain_scores_codex":[0.9999105,0.00001357158,0.000005884482,0.00002715712,0.00003123593,0.000011751],"domain_scores_gemma":[0.9997342,0.0001037276,0.00006144486,0.00001286215,0.00007109378,0.00001655633],"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":[0.0005368273,0.00009010838,0.01081817,0.00008327697,0.000006109089,0.00008915445,0.0002878743,0.004409954,0.9742484,0.0002318512,0.000131263,0.009067004],"study_design_scores_gemma":[0.00002447633,0.000917959,0.08911138,0.00002264079,0.00002551255,0.00008286921,0.0002603017,0.06737674,0.8410024,0.0001499893,0.0009800235,0.00004579781],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961309,0.0001248531,0.003168261,0.00001261056,0.000004708977,0.00001212555,0.000134386,0.00004002917,0.0003720853],"genre_scores_gemma":[0.9971647,0.00007217682,0.002013386,0.000006255823,0.000003152587,0.00001682251,0.000135544,0.000009030852,0.0005789116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001059542,"threshold_uncertainty_score":0.002670646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007318694408280405,"score_gpt":0.2028687368609472,"score_spread":0.1955500424526668,"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."}}