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Record W2094334301 · doi:10.1094/cfw-59-3-0120

Pulse Ingredients as Healthier Options in Extruded Products

2014· article· en· W2094334301 on OpenAlexafffund
Peter Fröhlich, G. Boux, Linda Malcolmson

Bibliographic record

VenueCereal Foods World · 2014
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsCanadian International Grains Institute
FundersSaskatchewan Pulse Growers
KeywordsBusinessExtrusionFood scienceChemistryBiochemical engineeringMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Pulse flours and outer pea hull fiber offer nutritional advantages over traditional flours and starches used in extruded products. Pulse flours are high in protein and micronutrients and, depending on whether they are made from whole or split seeds, contain high levels of fiber. The levels of starch present in pulse flours, although lower than those in traditional ingredients such as cornmeal, allow for moderate to good expansion of end products. Flour specifications should be considered when selecting pulse flours because milling method can impact both flour particle size and functionality. Yellow pea flour, which had higher levels of starch, showed greater expansion properties than lentil and chickpea flours. The addition of a coarser fiber fraction (outer pea hull fiber) to yellow pea flour, when blended at inclusion levels of 5 and 10%, resulted in minimal changes to the expansion properties of directly expanded products, while still enhancing fiber levels. Challenges encountered when including pulse ...

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.028
GPT teacher head0.288
Teacher spread0.260 · 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 designNot applicable
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

Citations17
Published2014
Admission routes2
Has abstractyes

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