{"id":"W3119572621","doi":"10.1108/hff-11-2020-0704","title":"Entropy generation and MHD analysis of a nanofluid with peristaltic three dimensional cylindrical enclosures","year":2021,"lang":"en","type":"article","venue":"International Journal of Numerical Methods for Heat &amp Fluid Flow","topic":"Nanofluid Flow and Heat Transfer","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Nanofluid; Mechanics; Peristalsis; Heat generation; Brinkman number; Magnetohydrodynamics; Entropy (arrow of time); Heat transfer; Thermophoresis; Stream function; Entropy production; Partial differential equation; Classical mechanics; Physics; Mathematics; Nusselt number; Mathematical analysis; Thermodynamics; Magnetic field; Turbulence; Chemistry; Reynolds number","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005298442,0.0002310552,0.0007176814,0.0004198882,0.00005845798,0.00006105333,0.0002045951,0.0001218585,0.000205687],"category_scores_gemma":[0.0002159878,0.0001847784,0.0004361636,0.0004715376,0.00007844382,0.0001827207,0.0000295895,0.000216974,0.000001135868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001136212,"about_ca_system_score_gemma":0.0001151689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001108088,"about_ca_topic_score_gemma":0.00001736881,"domain_scores_codex":[0.9979411,0.0001483842,0.000853201,0.0002348984,0.0005893858,0.0002330438],"domain_scores_gemma":[0.9980016,0.0005649964,0.00005928543,0.0001631148,0.001018345,0.0001926222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005121092,0.0002660453,0.003442069,0.00005310675,0.005502811,0.00005492585,0.0002806027,0.0624221,0.8989192,0.001253053,0.0003479637,0.02694598],"study_design_scores_gemma":[0.002248587,0.0005651311,0.006617303,0.0001049052,0.001786014,0.0004988611,0.00002592365,0.8710268,0.1094047,0.0007274381,0.006581387,0.0004130148],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2336333,0.002654474,0.7625141,0.0003510075,0.0006674698,0.00008847978,0.0000545014,0.0000171278,0.00001955745],"genre_scores_gemma":[0.3573549,0.0003026029,0.6416959,0.0001059877,0.0004098285,0.00001267455,0.00006279895,0.0000351805,0.00002012717],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8086047,"threshold_uncertainty_score":0.7535045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574948687593684,"score_gpt":0.3208926385357871,"score_spread":0.2951431516598503,"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."}}