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Record W2081798938 · doi:10.3168/jds.2008-1534

Phospholipid enrichment in sweet and whey cream buttermilk powders using supercritical fluid extraction

2009· article· en· W2081798938 on OpenAlexfundno aff
A. J. Spence, Rafael Jiménez‐Flores, Michael C. Qian

Bibliographic record

VenueJournal of Dairy Science · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsnot available
FundersOregon State UniversityUniversité Laval
KeywordsChemistryChromatographyFood sciencePhospholipidSupercritical fluidIngredientExtraction (chemistry)SphingomyelinWhey proteinSupercritical fluid extractionMicrofiltrationMembraneBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Milk fat globule membrane contains many complex lipids implicated in an assortment of biological processes. Microfiltration coupled with supercritical fluid extraction (SFE) has been shown to provide a method of concentrating these nutritionally valuable lipids into a novel ingredient. In the dairy industry there are several by-products that are rich in phospholipids (PL) such as buttermilk, whey, and whey cream. However, PL are present at low concentrations. To enrich PL in buttermilk powders, regular buttermilk and whey buttermilk (by-product of whey cream after making butter) were microfiltered and then treated with SFE after drying. The total fat, namely nonpolar lipids, in the powders was reduced by 38 to 55%, and phospholipids were concentrated by a factor of 5-fold. Characterization of the PL demonstrated specific molecular fatty amide combinations on the sphingosine (18:1) backbone of sphingomyelin with the greatest proportion being saturated; the most common were 16:0, 20:0, 21:0, 22:0, 23:0, and 24:0. Two unsaturated fatty amide chains, 23:1 and 24:1, were shown to be elevated in a whey cream buttermilk sample compared with the others. However, most unsaturated species were not as abundant.

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)0.001
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 score0.075
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.295
Teacher spread0.281 · 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

Citations43
Published2009
Admission routes1
Has abstractyes

Explore more

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