{"id":"W2341536190","doi":"10.1002/cjce.22504","title":"Cure kinetics characterization of soy‐based epoxy resins for infusion moulding process","year":2016,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Epoxy Resin Curing Processes","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ford Motor Company (Canada); University of Toronto","funders":"Centre for Bio-composite and Biomaterial Processing; University of Toronto","keywords":"Epoxy; Diglycidyl ether; Kinetics; Differential scanning calorimetry; Materials science; Bisphenol A; Isothermal process; Enthalpy; Composite material; Ultimate tensile strength; Chemical engineering; Polymer chemistry; Thermodynamics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0002546792,0.0003312726,0.0003347758,0.0002277397,0.000104191,0.0001822606,0.0001495066,0.0001931853,0.001012675],"category_scores_gemma":[0.0004347594,0.0001211382,0.0002949672,0.0001847178,0.00009494794,0.0002475232,0.00007654018,0.0003606189,0.0003376335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001292697,"about_ca_system_score_gemma":0.0001408815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005257973,"about_ca_topic_score_gemma":0.0006644112,"domain_scores_codex":[0.9998834,0.00001661297,0.000008607805,0.00002241816,0.00004956928,0.00001937368],"domain_scores_gemma":[0.999817,0.00006127146,0.00005222879,0.00001215932,0.00004231129,0.00001511948],"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":[0.00006738229,0.0000229284,0.0004004453,0.00005711885,0.000003173737,0.00002356757,0.00003748723,0.0005720832,0.9959807,0.00004604095,0.00001813556,0.002770773],"study_design_scores_gemma":[0.000002151979,0.0002047486,0.002837168,0.000004667567,0.000009271064,0.00002431152,0.0000224604,0.00456062,0.9918502,0.00001172436,0.0004662471,0.000006433108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913865,0.0007678639,0.006928534,0.00001777095,0.00001332957,0.00002115656,0.0002118201,0.0001005913,0.0005523865],"genre_scores_gemma":[0.9949225,0.0005152737,0.003174033,0.000005637005,0.000003176469,0.0000162098,0.0001847005,0.00003416016,0.001144344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001012675,"threshold_uncertainty_score":0.003387749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009888812036073754,"score_gpt":0.2050479677277708,"score_spread":0.1951591556916971,"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."}}