{"id":"W2616575129","doi":"10.1016/j.jfoodeng.2017.05.018","title":"The role of nonlinear viscoelasticity on the functionality of laminating shortenings","year":2017,"lang":"en","type":"article","venue":"Journal of Food Engineering","topic":"Food Chemistry and Fat Analysis","field":"Agricultural and Biological Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Argonne National Laboratory; Office of Science","keywords":"Rheology; Viscoelasticity; Nonlinear system; Materials science; Composite material; Dynamic modulus; Dynamic mechanical analysis; Polymer; 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":[0.000378187,0.00005284529,0.0001165997,0.000004320795,0.0001798856,0.00002792923,0.0003042039,0.00002727494,0.0000132305],"category_scores_gemma":[0.0003826056,0.00001497311,0.0001344969,0.00004949074,0.00003385501,0.00005275481,0.00003210099,0.0001374707,1.846979e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006615438,"about_ca_system_score_gemma":0.000003624631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007951654,"about_ca_topic_score_gemma":0.000007708737,"domain_scores_codex":[0.9994601,0.000009198855,0.0002266251,0.00004065672,0.0001879272,0.00007551769],"domain_scores_gemma":[0.999154,0.0003142282,0.0003437974,0.00005610149,0.0001079165,0.00002399925],"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":[0.00003050453,0.00003702873,0.002165656,0.00000799366,0.000126241,5.875307e-7,0.0000379295,0.001270514,0.9831536,0.0006048846,0.00001164902,0.01255335],"study_design_scores_gemma":[0.00009192,0.0006666059,0.09418488,0.0001220769,0.00007074782,0.00001095717,0.0004740416,0.008825635,0.8931254,0.0004086926,0.001923798,0.00009521669],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990684,0.0001071669,0.00002272691,0.0003592206,0.00004942171,0.00001347737,0.00000491016,0.000002040939,0.0003726207],"genre_scores_gemma":[0.9997087,0.00001183743,0.00007352185,0.000003508854,0.0001927333,2.641956e-7,3.301931e-7,4.098652e-7,0.000008694266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09201922,"threshold_uncertainty_score":0.1383553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01149599289429902,"score_gpt":0.1919465277851589,"score_spread":0.1804505348908599,"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."}}