{"id":"W3184032527","doi":"10.1080/15376494.2021.1952496","title":"A master curve approach to model short- and long-term time-dependent nonlinear behavior of polyethylene","year":2021,"lang":"en","type":"article","venue":"Mechanics of Advanced Materials and Structures","topic":"Polymer crystallization and properties","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Creep; Viscoplasticity; Viscoelasticity; Constitutive equation; Nonlinear system; Term (time); Materials science; Power law; Phenomenological model; Work (physics); Stress (linguistics); Mechanics; Structural engineering; Mathematics; Engineering; Mechanical engineering; Composite material; Physics; Finite element method; Statistics","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":[0.0003960406,0.0007367462,0.0003903781,0.000867718,0.0003013719,0.000460825,0.0008669453,0.0008533197,0.001269635],"category_scores_gemma":[0.0009787948,0.0003156785,0.0007557783,0.000520859,0.0004752892,0.00153282,0.000473229,0.0009617332,0.0005285668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005535022,"about_ca_system_score_gemma":0.0007400759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001238696,"about_ca_topic_score_gemma":0.001289249,"domain_scores_codex":[0.9998204,0.00002268605,0.00001018571,0.00003744437,0.00009302363,0.00001644349],"domain_scores_gemma":[0.9996585,0.0001231818,0.00006173411,0.00006159586,0.00007632478,0.00001875108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004178619,0.000192964,0.00159646,0.000189399,0.00004790207,0.000232904,0.0003551383,0.6856202,0.114132,0.116087,0.001036972,0.08046736],"study_design_scores_gemma":[0.000002628578,0.00005492985,0.0003369972,0.00001100187,0.000007598358,0.00009245526,0.00001623547,0.9722108,0.009304765,0.01121924,0.00672584,0.0000174993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01532014,0.0003117257,0.9809811,0.00006864606,0.00003745675,0.00005600356,0.00006422408,0.0002282252,0.002932491],"genre_scores_gemma":[0.6411189,0.003388788,0.3229476,0.0001444223,0.0001752087,0.000581232,0.0003753424,0.0005069047,0.03076154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001269635,"threshold_uncertainty_score":0.004247367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240149541831613,"score_gpt":0.2537854497857993,"score_spread":0.2313839543674832,"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."}}