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Record W2049090729 · doi:10.1094/cchem-86-4-0470

A Comparative Study Between the McGill #2 Laboratory Mill and Commercial Milling Systems

2009· article· en· W2049090729 on OpenAlexaboutno aff
A. M. Graves, T. J. Siebenmorgen, Mohammed Saleh

Bibliographic record

VenueCereal Chemistry · 2009
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
Fundersnot available
KeywordsBranRoller millViscosityChemistryFood scienceMillMaterials scienceComposite materialRaw material

Abstract

fetched live from OpenAlex

ABSTRACT The degree of similarity between rice milled in a McGill #2 laboratory mill and commercial milling processes was evaluated using eight physical, physicochemical, and end‐use properties. There was no statistical difference between the two milling systems with respect to color parameters L * and a *, final viscosity, texture, and end‐use cooking properties (α = 0.05). Overall, the kernel dimensions of length, width, and thickness were less in the McGill #2 laboratory‐milled rice than the same rice milled commercially. The incidence of bran streaks and peak viscosity values were each higher when the rice sample was milled commercially in 27, and 28, respectively, of the 29 samples by means comparison. The decrease in kernel dimensions and incidence of bran streaks were attributed to the more aggressive nature of the single‐pass, batch milling system of the McGill #2 laboratory mill as compared with multipass, continuous milling systems that are used commercially. Finally, as surface lipid content (SLC) decreased, L * increased and a *, b *, and the incidence of bran streaks decreased for both milling systems.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.423

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 head0.041
GPT teacher head0.288
Teacher spread0.247 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

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