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Record W4318484722 · doi:10.3390/dairy4010008

Effect of the Heat Exchanger Type on Stirred Yogurt Properties Formulated at Different Total Solids and Fat Contents

2023· article· en· W4318484722 on OpenAlexaff
Noémie Lussier, Audrey Gilbert, Daniel St‐Gelais, Sylvie L. Turgeon

Bibliographic record

VenueDairy · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversité LavalAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSyneresisLactoseFood scienceChemistrySkimmed milkViscosityTotal dissolved solidsRheologyApparent viscosityRaw materialRaw milkHeat exchangerMaterials scienceThermodynamicsComposite material

Abstract

fetched live from OpenAlex

In this work stirred yogurts were produced using a technical scale pilot in which the cooling step was processed using either a tubular (THX; low shear) or a plate (PHX, high shear) heat exchanger. The aim was to determine how total solids (TS, adjusted using lactose) and fat contents (FC) impact stirred yogurt properties during storage, depending on the heat exchanger used. Using raw milk, cream, skim milk powder, and lactose, four yogurts were formulated at 16.5% TS and 4.2% proteins, with different FC (0.0, 1.3, 2.6, and 3.9%); one more control yogurt was formulated at 14% TS, 4.2% proteins, and 0.0% FC. Analyses of yogurts (firmness, viscosity, induced syneresis) were realized at days 1, 3, 7, 21, and 34 after production. The addition of lactose between the non-fat yogurt at 14 or 16.5% TS had little to no effect on stirred yogurt properties. Increasing FC reduced syneresis while increasing firmness and viscosity. The use of PHX reduced the syneresis compared to THX; however, it also tended to reduce the firmness of the yogurts with 3.9% FC.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.106

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 head0.068
GPT teacher head0.257
Teacher spread0.190 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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