{"id":"W4390583811","doi":"10.1080/10407782.2023.2292197","title":"Computing neural network to analyze heat and mass transfer in the flow of nanofluid between two disks","year":2024,"lang":"en","type":"article","venue":"Numerical Heat Transfer Part A Applications","topic":"Nanofluid Flow and Heat Transfer","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Nanofluid; Nusselt number; Mechanics; Artificial neural network; Sherwood number; Materials science; Flow (mathematics); Heat transfer; Partial differential equation; Nonlinear system; Computer science; Mathematics; Reynolds number; Physics; Mathematical analysis; Artificial intelligence; Turbulence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002972673,0.0003201214,0.000491039,0.0001431841,0.000138794,0.00007771846,0.000292472,0.0001222242,0.00004999151],"category_scores_gemma":[0.000001508645,0.0002586042,0.0001850506,0.001463674,0.00008312979,0.0001052254,0.000008808921,0.000441054,0.00002982485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004356696,"about_ca_system_score_gemma":0.00002514222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006694658,"about_ca_topic_score_gemma":0.00005024402,"domain_scores_codex":[0.9979624,0.00008578382,0.0006489236,0.0004440378,0.0002847218,0.0005740884],"domain_scores_gemma":[0.9990265,0.0003806348,7.753387e-7,0.0003545214,0.00002865819,0.0002089525],"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":[0.0002120035,0.0005182747,0.02847585,0.002359537,0.0008806809,0.00005748307,0.01408885,0.6418804,0.1570052,0.02814725,0.004816056,0.1215584],"study_design_scores_gemma":[0.001935527,0.000553065,0.01742286,0.0005791304,0.0007103443,0.00003885921,0.0002555418,0.817833,0.02043776,0.001078363,0.1374738,0.001681723],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2104411,0.002701652,0.7834421,0.001334181,0.0001223959,0.001061464,0.000146749,0.00025154,0.0004987789],"genre_scores_gemma":[0.9977514,0.0001965515,0.0008578553,0.0002157912,0.0004508068,0.0003988585,0.00005848579,0.00006443827,0.000005863442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7873102,"threshold_uncertainty_score":0.9999866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01598905129236236,"score_gpt":0.2613441878120417,"score_spread":0.2453551365196794,"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."}}