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Record W2040124291 · doi:10.3390/foods2040444

Behavior of Heat-Denatured Whey: Buttermilk Protein Aggregates during the Yogurt-Making Process and Their Influence on Set-Type Yogurt Properties

2013· article· en· W2040124291 on OpenAlexafffund
Maxime Saffon, Véronique Richard, Rafael Jiménez‐Flores, Sylvie F. Gauthier, Michel Britten, Yves Pouliot

Bibliographic record

VenueFoods · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsAgriculture and Agri-Food CanadaUniversité Laval
FundersNational Institutes of HealthMinistère de l'Agriculture et de l'AlimentationMinistry of Agriculture - SaskatchewanUniversité Laval
KeywordsChemistrySkimmed milkFood scienceWhey proteinWhey protein isolateConfocal laser scanning microscopyCaseinProtein aggregationSodium CaseinateChromatographyBiochemistryBiophysics

Abstract

fetched live from OpenAlex

The objective of this study was to assess the impact of using heat-denatured whey:buttermilk protein aggregate in acid-set type yogurt production. Whey and buttermilk (25:75) protein concentrate was adjusted to pH 4.6, heated at 90 °C for 5 min, homogenized and freeze-dried. Set-type yogurts were prepared from skim milk standardized to 15% (w/v) total solids and 4.2% (w/v) protein using different levels of powdered skim milk or freeze-dried protein aggregate. The use of the protein aggregate significantly modified yogurt texture, but did not affect the water-holding capacity of the gel. Confocal laser-scanning microscope images showed the presence of large particles in milk enriched with protein aggregate, which directly affected the homogeneity of the clusters within the protein matrix. Thiol groups were freed during heating of the protein aggregate suspended in water, suggesting that the aggregates could interact with milk proteins during heating.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.229
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2013
Admission routes2
Has abstractyes

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