{"id":"W3156788862","doi":"10.1016/j.ijbiomac.2021.03.190","title":"Catechin-grafted arabinoxylan conjugate: Preparation, structural characterization and property investigation","year":2021,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Food composition and properties","field":"Nursing","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Tianjin Science and Technology Committee; Beijing Technology and Business University; Beijing Engineering and Technology Research Center of Food Additives","keywords":"Arabinoxylan; Chemistry; Covalent bond; Catechin; Conjugate; Thermal stability; Grafting; Pectin; Substrate (aquarium); Starch; Polysaccharide; Polyphenol; Nuclear chemistry; Organic chemistry; Food science; Antioxidant; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009474833,0.0001801034,0.00009480951,0.0001602001,0.0001264172,0.0001258103,0.00008184077,0.0001409074,0.0005110265],"category_scores_gemma":[0.0001381566,0.00006883006,0.0001195848,0.0001916494,0.0001269034,0.000128425,0.00006557986,0.000208386,0.0001277384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001177137,"about_ca_system_score_gemma":0.0001354851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004425356,"about_ca_topic_score_gemma":0.0006776869,"domain_scores_codex":[0.9999596,0.000004759574,0.000002533346,0.00001024737,0.0000129143,0.00001007566],"domain_scores_gemma":[0.9999435,0.000009500942,0.00001533963,0.000007516257,0.00001446059,0.000009682983],"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":[0.00003621307,0.000009740734,0.0001579166,0.0000133965,0.000002155076,0.00002018951,0.00001260346,0.00009735863,0.9988515,0.0000344868,0.00000834178,0.0007561353],"study_design_scores_gemma":[0.000001485912,0.0001226197,0.001872886,0.000001302238,0.000008485903,0.00004043975,0.000009110324,0.0004140148,0.9969679,0.000009191484,0.0005499368,0.000002592644],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973671,0.0002200025,0.001749146,0.00001737205,0.000006523072,0.00001358413,0.00006351002,0.00001372393,0.0005490749],"genre_scores_gemma":[0.9961481,0.0002511778,0.001869085,0.00001674347,0.000003012605,0.00001071676,0.00009764605,0.000008303492,0.001595334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005110265,"threshold_uncertainty_score":0.001709521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02295298141289254,"score_gpt":0.2712779804966635,"score_spread":0.248324999083771,"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."}}