{"id":"W2890356370","doi":"10.1063/1.5045739","title":"Modeling polymer extrusion with varying die gap using Arbitrary Lagrangian Eulerian (ALE) method","year":2018,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Die swell; Extrusion; Reynolds number; Mechanics; Physics; Free surface; Eulerian path; Newtonian fluid; Transient (computer programming); Die (integrated circuit); Finite element method; Classical mechanics; Lagrangian; Mechanical engineering; Materials science; Turbulence; Thermodynamics; Composite material; Computer science; Engineering","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":[0.0001568487,0.0002361983,0.0003840961,0.00005985868,0.0001880993,0.00001011207,0.0001896254,0.0001041629,0.00002374492],"category_scores_gemma":[0.00002160939,0.0002089706,0.0001090341,0.0002043533,0.0001560411,0.0002167287,0.0001334188,0.0002080425,0.000008369291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003035158,"about_ca_system_score_gemma":0.00002958942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001763223,"about_ca_topic_score_gemma":0.000004781253,"domain_scores_codex":[0.9988415,0.00003459306,0.0002809556,0.0003033484,0.0001872935,0.0003523387],"domain_scores_gemma":[0.9993556,0.00008500089,0.00005348958,0.0003087522,0.0001283444,0.0000687695],"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":[0.0001058018,0.00006031398,0.0002344779,0.00006593645,0.0001845233,0.000004729673,0.001027327,0.01774118,0.9578008,0.02111092,0.000003461312,0.00166054],"study_design_scores_gemma":[0.0003382328,0.0000541322,0.00001154818,0.0001078004,0.00008264156,0.000004811058,0.00004095354,0.8561154,0.1411822,0.001836037,0.000002761232,0.0002235334],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2316768,0.0006236472,0.7639449,0.00003619872,0.000112014,0.00006584206,0.000007689672,0.00007578832,0.003457139],"genre_scores_gemma":[0.8891963,0.00003742404,0.11009,0.00007080854,0.0004199794,0.000004973315,0.000009282021,0.00005017385,0.0001209761],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8383742,"threshold_uncertainty_score":0.8521572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02957644660961161,"score_gpt":0.2767958879989659,"score_spread":0.2472194413893543,"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."}}