{"id":"W2971643969","doi":"10.1016/j.foodhyd.2019.105353","title":"Food-grade strategies to increase stability of whey protein particles: Particle hardening through aldehyde treatment","year":2019,"lang":"en","type":"article","venue":"Food Hydrocolloids","topic":"Proteins in Food Systems","field":"Agricultural and Biological Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Wetenschappelijk Onderzoek","keywords":"Vanillin; Chemistry; Isoelectric point; Syringaldehyde; Chromatography; Aqueous solution; Particle size; Chemical engineering; Whey protein isolate; Maghemite; Salicylaldehyde; Hexanal; Organic chemistry; Whey protein; Polymer chemistry; Mineralogy","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":[0.0003705115,0.0002947067,0.0004839928,0.00001275899,0.0001498062,0.0001125265,0.0004095036,0.0001255345,0.0002977622],"category_scores_gemma":[0.00006312558,0.0001309353,0.0001877651,0.0004649662,0.00007556831,0.0003706737,0.0001481774,0.00009920907,0.0001739209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001408669,"about_ca_system_score_gemma":0.00005337283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001265991,"about_ca_topic_score_gemma":0.002874699,"domain_scores_codex":[0.9975815,0.0002530848,0.0005636027,0.0005778821,0.0004449477,0.0005789624],"domain_scores_gemma":[0.9991257,0.00009796028,0.0001853678,0.0002955778,0.00008198099,0.0002134564],"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":[0.0001842736,0.0004431647,0.01022648,0.00004459075,0.00008345288,0.000001380674,0.001301507,0.00008386888,0.9846489,0.001463618,0.00002332939,0.001495391],"study_design_scores_gemma":[0.000742995,0.0168652,0.006375941,0.00008633158,0.0000262077,0.000003699978,0.003892926,0.0001498862,0.9628847,0.001904649,0.006676597,0.0003908847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939861,0.0001708853,0.00001380984,0.0005174697,0.00008219912,0.003643385,0.0001197038,0.0001520488,0.001314438],"genre_scores_gemma":[0.998462,0.000002363186,0.0003481741,0.0000522863,0.0001177191,0.0008510035,0.00001217666,0.000004398838,0.0001498307],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02176426,"threshold_uncertainty_score":0.5339386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04709313806938214,"score_gpt":0.2508775453873083,"score_spread":0.2037844073179261,"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."}}