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Effect of milling method on selected physical and functional properties of cowpea (<i>Vigna unguiculata</i>) paste

2005· article· en· W1971718406 on OpenAlexaff
Amandip Singh, Yen‐Con Hung, Milena Corredig, R. Dixon Phillips, Manjeet S. Chinnan, Kay H. McWatters

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2005
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsVignaMathematicsMaterials scienceAgronomyBiology

Abstract

fetched live from OpenAlex

Abstract Particle size distribution (PSD) of cowpea meal is an important determinant of paste functionality and end product quality. Samples from various mills and screen sizes were used to determine PSD, water-holding capacity (WHC) and swelling capacity (SWC). Hammer mill (1.73 mm screen) meal had a geometric mean diameter (dgw) of 221 microns, whereas PM-360 [plate mill with one complete turn (360°) of clearance] meal had a dgw of 1559 microns. All other milling processes resulted in meal with an intermediate particle size. To reduce the particle size of cowpea pastes, cowpea meals were hydrated to pre-determined moisture contents, held for 15 min, and then blended in a blender before whipping. Blending increased the WHC and SWC of all samples.

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 score0.050
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.016
GPT teacher head0.287
Teacher spread0.271 · 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

Citations37
Published2005
Admission routes1
Has abstractyes

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