{"id":"W2921899105","doi":"10.1016/j.polymdegradstab.2019.03.001","title":"Synthesis and thermo-mechanical properties of novel spirobiindane based epoxy nanocomposites with tryptophan as a green hardener: Curing kinetics using model free approach","year":2019,"lang":"en","type":"article","venue":"Polymer Degradation and Stability","topic":"Epoxy Resin Curing Processes","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Thermogravimetric analysis; Materials science; Epoxy; Nanocomposite; Curing (chemistry); Differential scanning calorimetry; Fourier transform infrared spectroscopy; Composite material; Epichlorohydrin; Exfoliation joint; Scanning electron microscope; Chemical engineering; Polymer chemistry; Graphene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001372178,0.0002319224,0.0001377226,0.0001039275,0.00008064124,0.0001500685,0.0001669521,0.0001918499,0.0006090979],"category_scores_gemma":[0.0001654952,0.0001469586,0.0001270816,0.00008716471,0.000089724,0.0002158152,0.00009739882,0.0002981554,0.0002263448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001285953,"about_ca_system_score_gemma":0.0001000547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002348786,"about_ca_topic_score_gemma":0.0005877074,"domain_scores_codex":[0.9999341,0.000005795676,0.000006085517,0.00001900545,0.00002005146,0.00001497747],"domain_scores_gemma":[0.999904,0.00001901829,0.00003479212,0.000007732706,0.00001961378,0.00001471408],"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":[0.0000189831,0.000006475585,0.00003122086,0.00001327907,9.89536e-7,0.0000102836,0.000008509529,0.00005446537,0.9993271,0.00002482748,0.000006186895,0.0004978827],"study_design_scores_gemma":[0.000001245737,0.00004497381,0.0003575957,8.757884e-7,0.000002763205,0.00001332362,0.000003522289,0.0005060796,0.998858,0.000005273159,0.0002044592,0.000002030808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937088,0.000514756,0.004968998,0.00002094931,0.000009118405,0.0000105537,0.00007047376,0.00004758835,0.0006487264],"genre_scores_gemma":[0.9935688,0.000296668,0.003784309,0.000009658247,0.000002724561,0.00001570534,0.00008824022,0.00002418176,0.002209667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006090979,"threshold_uncertainty_score":0.002037644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03310461389398848,"score_gpt":0.2097691928604629,"score_spread":0.1766645789664744,"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."}}