{"id":"W4285092853","doi":"10.1515/ipp-2021-4214","title":"Calendering of thermoplastics: models and computations","year":2022,"lang":"en","type":"article","venue":"International Polymer Processing","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Calendering; Materials science; Lubrication; Viscoplasticity; Composite material; Shear thinning; Finite element method; Dissipation; Rheology; Constitutive equation; Mechanics; Thermodynamics; Physics","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":[0.00004274408,0.00005412496,0.00007426486,0.00006107104,0.0001222611,0.00000609276,0.00009264852,0.00001427535,0.00004380791],"category_scores_gemma":[0.00001293153,0.00005778597,0.00001750879,0.0000503329,0.00005224652,0.00007861538,0.0001534177,0.0001042175,4.278801e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002207849,"about_ca_system_score_gemma":0.00001422966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001453448,"about_ca_topic_score_gemma":9.077837e-7,"domain_scores_codex":[0.9995625,0.000006974275,0.0001342561,0.00009787715,0.0001245044,0.00007388853],"domain_scores_gemma":[0.9998161,0.00005445065,0.00004698676,0.00003189607,0.00003541939,0.00001516671],"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":[0.00004294404,0.00008292103,0.003371924,0.00006797046,0.0001613389,0.000006679612,0.003254208,0.7789052,0.07657374,0.1233381,0.00002926726,0.01416571],"study_design_scores_gemma":[0.0001486653,0.000007187808,0.0001959315,0.00001184422,0.000007452541,0.00001798772,0.0002702252,0.9957073,0.001695873,0.001867836,0.00001107504,0.00005857859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1758291,0.002657633,0.8144963,0.0003525716,0.000234247,0.00003250228,0.00003503714,0.00005426852,0.006308324],"genre_scores_gemma":[0.9981679,0.000009672178,0.0009698857,0.00005006698,0.00002855605,0.00001180762,0.000007655062,0.000008425628,0.0007460028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8223388,"threshold_uncertainty_score":0.2356444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01529586423671742,"score_gpt":0.2452158953383086,"score_spread":0.2299200311015912,"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."}}