{"id":"W7133026716","doi":"","title":"Tunable Tensile Properties of Polypropylene (PP) and Polyethylene Terephthalate (PET) Fibrillar Blend Through Micro-/Nano-layered Extrusion Technology","year":2020,"lang":"","type":"dissertation","venue":"TSpace","topic":"Polymer crystallization and properties","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Extrusion; Polypropylene; Polyethylene terephthalate; Ultimate tensile strength; Yield (engineering); Melt flow index; Shear (geology); Tensile testing; Elastic modulus; Polyethylene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001393837,0.0002144636,0.0001157072,0.0001155328,0.00008409173,0.0001525834,0.0000843332,0.0001444444,0.0005794813],"category_scores_gemma":[0.0001318111,0.0001096982,0.000132483,0.00009949132,0.00009795218,0.0002613323,0.00009188422,0.0002498421,0.0001666692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007914114,"about_ca_system_score_gemma":0.00005111677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009069803,"about_ca_topic_score_gemma":0.0003202873,"domain_scores_codex":[0.9999311,0.000006760869,0.000005071674,0.00001595162,0.00002906614,0.00001196332],"domain_scores_gemma":[0.9999037,0.00002274119,0.00004001683,0.000006795324,0.0000163574,0.0000104234],"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":[0.00001013791,0.000004271807,0.0000651337,0.000009719818,9.277595e-7,0.00001406985,0.000005559867,0.00003020967,0.9993824,0.000009041009,0.00000330927,0.0004652661],"study_design_scores_gemma":[0.00000139855,0.00007372275,0.002543332,0.000001394635,0.00000397166,0.00005148145,0.000006895772,0.0003459741,0.9965647,0.000004523531,0.0004008962,0.000001772022],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954781,0.0004555142,0.003187985,0.00001726613,0.000007609419,0.000006505039,0.00004778551,0.00002778098,0.0007714872],"genre_scores_gemma":[0.9940838,0.0003935151,0.004034745,0.00001530157,0.000004677445,0.00001119807,0.00009731972,0.00001985721,0.0013396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005794813,"threshold_uncertainty_score":0.001938522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043480747266403,"score_gpt":0.2795298800725888,"score_spread":0.2490950725999248,"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."}}