{"id":"W4391913030","doi":"10.1016/j.foodres.2024.114133","title":"Microencapsulation of ultrasound-assisted phenolic extracts of sugar maple leaves: Characterization, in vitro gastrointestinal digestion, and storage stability","year":2024,"lang":"en","type":"article","venue":"Food Research International","topic":"Microencapsulation and Drying Processes","field":"Agricultural and Biological Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Islamic Development Bank","keywords":"Chemistry; Nutraceutical; Food science; Pomace; Sugar; Maltodextrin; Antioxidant; Chromatography; Solubility; Bioavailability; Whey protein isolate; Maceration (sewage); Spray drying; Whey protein; Biochemistry; Materials science; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007145904,0.00008627729,0.0001236897,0.0001177602,0.0000614806,0.00008449314,0.0001801928,0.00005536612,0.0004251052],"category_scores_gemma":[0.0006620793,0.00004656601,0.00003617009,0.0005197524,0.0001582824,0.0002492392,0.00005790405,0.0002260129,0.000004386819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005956544,"about_ca_system_score_gemma":0.00005117426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001118259,"about_ca_topic_score_gemma":0.0001074869,"domain_scores_codex":[0.9986212,0.0001337176,0.000364478,0.0002638356,0.0004352197,0.0001815973],"domain_scores_gemma":[0.9988379,0.0004716462,0.0000841893,0.00004774361,0.0005010934,0.00005738476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008388521,0.0001293337,0.01750227,0.00007707044,0.00000892022,0.000001659907,0.0002557446,0.000005026413,0.9763585,0.0005836556,0.00003885425,0.004955073],"study_design_scores_gemma":[0.000150871,0.0002131753,0.7823715,0.0002168556,0.000002562553,0.00003588445,0.0002628623,0.0006528441,0.2138489,0.0007682244,0.00139386,0.00008256383],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979044,0.0001392602,0.0001951082,0.0008646722,0.00008139784,0.0001722376,0.0004023477,0.00002527094,0.0002152894],"genre_scores_gemma":[0.9989315,0.00004294101,0.0002593114,0.000009632281,0.0000853409,0.00001092431,0.0005502676,0.000001639542,0.0001085008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7648692,"threshold_uncertainty_score":0.4654604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06636792098310303,"score_gpt":0.3078058116388684,"score_spread":0.2414378906557654,"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."}}