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Record W2959406345 · doi:10.3168/jds.2019-16547

Short communication: Determination of the whey protein index in milk protein concentrates

2019· article· en· W2959406345 on OpenAlexafffund
Zhengtao Zhao, Milena Corredig, Zafir Gaygadzhiev

Bibliographic record

VenueJournal of Dairy Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Guelph
FundersMitacs
KeywordsSkimmed milkCaseinChemistryWhey proteinFood scienceMilk proteinSolubilizationChromatographyBiochemistry

Abstract

fetched live from OpenAlex

Milk protein concentrates are common ingredients in the dairy industry, with varying processing histories and composition. The objective of this research was to determine the feasibility of using the whey protein nitrogen (WPN) index, a well-established index for skim milk powder and nonfat dry milk, as a quality parameter for milk protein concentrates. The WPN index is a value based on the moisture-adjusted weight of skim milk powder. We hypothesized that WPN, even when standardized based on protein, may change depending on solubilization conditions of milk protein concentrates because of differences in solubilization conditions or processing history. The WPN was measured for model concentrates with different thermal history or reconstitution conditions. The WPN was not affected by an increased concentration of soluble casein in the dispersions nor after solubilization of the powder at 22 or 60°C. All reconstituted samples were standardized for protein. The WPN was also in full accordance with residual native protein measured by chromatography.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.001

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 head0.022
GPT teacher head0.248
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2019
Admission routes2
Has abstractyes

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