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Record W6981415580

Effect of Polyethylene Glycol 3350 on the Handling Properties of Low Salt Wheat Dough Formulations

2019· other· en· W6981415580 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2019
Typeother
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPEG ratioCultivarPolyethylene glycolRheologyWater contentWater activityPolyethyleneSodiumWheat flourMixing (physics)
DOInot available

Abstract

fetched live from OpenAlex

The effect of polyethylene glycol (PEG) 3350 addition (3%, flour wt. basis) on the properties of dough made from two Canadian Western Red Spring wheat cultivars (Triticum aestivum L. ‘Harvest’ and ‘Pembina’) differing in dough mixing requirements and dough-handling properties was investigated in a low salt dough formulation (1% NaCl, flour wt. basis). PEG was added for experimental purposes to alter water mobility to better understand underlining mechanisms, however would not be used in real bread formulations. For cultivar Harvest, but not Pembina, dough stickiness was reduced by the addition of PEG. Dough freezable water content decreased with the addition of PEG for both cultivars. Rheological measurements showed that PEG increased dough stiffness as measured by the complex modulus 'G*'. Creep measurements indicated that the relative elastic component (Jel) increased whereas maximum deformation (Jmax) decreased with the addition of PEG for cultivar Harvest only. Dough made with a weaker cultivar (Harvest) with the addition of PEG performed similarly to dough made with a stronger cultivar (Pembina) without PEG. Results indicate that in a low sodium environment, availability of water is critically important for controlling a number of properties that relate closely to dough machinability, especially in a weaker wheat cultivar.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication, Open science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.145
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0110.013
Science and technology studies0.0000.001
Scholarly communication0.0080.066
Open science0.0210.018
Research integrity0.0000.002
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 head0.106
GPT teacher head0.360
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

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