{"id":"W2939429748","doi":"10.1039/c9ra00769e","title":"Chitin nano-whiskers (CNWs) as a bio-based bio-degradable reinforcement for epoxy: evaluation of the impact of CNWs on the morphological, fracture, mechanical, dynamic mechanical, and thermal characteristics of DGEBA epoxy resin","year":2019,"lang":"en","type":"article","venue":"RSC Advances","topic":"Polymer composites and self-healing","field":"Materials Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Public Health","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; Universities Space Research Association","keywords":"Epoxy; Composite material; Materials science; Fracture toughness; Whiskers; Toughness; Izod impact strength test; Ultimate tensile strength; Glass transition; Whisker; Polymer","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":[0.0001636556,0.0003651266,0.0001340808,0.0001686634,0.00009996596,0.0001645412,0.000115463,0.0002811867,0.0006986397],"category_scores_gemma":[0.0001598424,0.0001542757,0.0001757308,0.0001345499,0.0001452811,0.0001817374,0.0001079403,0.0002996992,0.0001307171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042708,"about_ca_system_score_gemma":0.00006962686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004830771,"about_ca_topic_score_gemma":0.002177416,"domain_scores_codex":[0.9998834,0.00001210463,0.000009340451,0.00002628663,0.0000492537,0.00001966976],"domain_scores_gemma":[0.9998354,0.00004039803,0.00005544563,0.000009635401,0.00003270163,0.00002647375],"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":[0.00001187366,0.000004620488,0.00005039852,0.00001785392,0.000001131278,0.00001653048,0.000006181658,0.00003245748,0.9995797,0.000004417221,0.000003174231,0.0002716991],"study_design_scores_gemma":[9.701149e-7,0.0001081592,0.001731869,0.000002168887,0.000004380654,0.00003182761,0.00001329816,0.0002470964,0.9976889,0.000003124634,0.0001658863,0.000002353088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976397,0.0004353962,0.001339124,0.000012329,0.00001098262,0.00001701582,0.0001049561,0.00002230106,0.0004183902],"genre_scores_gemma":[0.9947308,0.0004491655,0.003489568,0.00001541369,0.00000245408,0.0000251574,0.0001084298,0.00001723345,0.001161745],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006986397,"threshold_uncertainty_score":0.002337158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02047950975809477,"score_gpt":0.2992377733878269,"score_spread":0.2787582636297322,"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."}}