{"id":"W4214830708","doi":"10.1016/j.foodchem.2022.132618","title":"Reinforcing canola protein matrix with chemically tailored nanocrystalline cellulose improves the functionality of canola protein-based packaging materials","year":2022,"lang":"en","type":"article","venue":"Food Chemistry","topic":"Nanocomposite Films for Food Packaging","field":"Materials Science","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Manitoba","funders":"","keywords":"Canola; Nanocrystalline material; Biopolymer; Cellulose; Ultimate tensile strength; Chemical engineering; Chemistry; Nanomaterials; Food packaging; Materials science; Nanotechnology; Food science; Organic chemistry; Composite material; Polymer","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008624725,0.0004400059,0.0005066019,0.00005401726,0.0005145249,0.0001468266,0.0009165127,0.0001077725,0.001442691],"category_scores_gemma":[0.00007194428,0.0003488943,0.0001316592,0.0004533518,0.0002666304,0.0001591441,0.0004417505,0.0004015995,0.000007114229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003318142,"about_ca_system_score_gemma":0.0006740019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003376136,"about_ca_topic_score_gemma":0.00001077623,"domain_scores_codex":[0.996667,0.0001315343,0.0008130499,0.0006868369,0.001026522,0.0006750038],"domain_scores_gemma":[0.9977923,0.00007026198,0.0008248656,0.0009524918,0.0002167466,0.0001433137],"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":[0.0007423938,0.0001069686,0.0000447292,0.0007472861,0.00005359283,0.00001268612,0.0001540787,0.0005457259,0.9974255,0.00005564262,0.00008703795,0.00002434628],"study_design_scores_gemma":[0.001152645,0.0003890883,0.00001762155,0.0001810985,0.00005751705,0.00004036365,0.0002451851,0.0001102336,0.9965286,0.00009206081,0.0007437009,0.0004418879],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967583,0.0001267561,0.0002219861,0.0003935076,0.000120114,0.001286911,0.000447177,0.0001976794,0.0004475489],"genre_scores_gemma":[0.9953195,2.059692e-7,0.001877692,0.00005558172,0.0001466664,0.0008479616,0.0002392157,0.00008068404,0.00143248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001655706,"threshold_uncertainty_score":0.9998963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007019788115808868,"score_gpt":0.2026345487481719,"score_spread":0.195614760632363,"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."}}