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Record W2765786590 · doi:10.1111/ijfs.13581

Red–Green–Blue (<scp>RGB</scp>) colour system approach to study the segregation and percolation in a mixture of white wheat flour and bleached wheat bran

2017· article· en· W2765786590 on OpenAlexaff
Amara Aït‐Aissa, Meriem Zaddem, Mohammed Aïder

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2017
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBranWheat flourFood scienceRGB color modelChemistryHomogeneousMathematicsMaterials scienceChromaticityRaw materialComputer scienceCombinatoricsOrganic chemistryArtificial intelligence

Abstract

fetched live from OpenAlex

Summary In this work, we applied a nonintrusive measurement method based on the Red–Green–Blue ( RGB ) image analysis system to study the segregation and percolation in a mixture of white wheat flour and bleached wheat bran. This method intended to quantify the presence of one or several colours in the surface of mixed ingredients. The mixing of flour particles with bleached and unbleached wheat bran was studied using a 90 mm closed rotating cube. This system forced the particles to roll relative to each other so as to favourite the segregation by percolation in order to hide one colour by another. The obtained results showed a possibility of obtaining homogeneous colour when the wheat flour was mixed with the bleached wheat bran at a volume ratio of 20/5%–10%. By increasing to ratio up to 20/15% (flour/bran), the RGB system showed a presence of two colours in the surface of the mixture. Moreover, the RGB method confirmed the presence of two heterogeneous colours when the wheat flour was mixed with the unbleached wheat bran whatever the ratio (20/5%, 10% and 15%).

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)0.001
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 score0.294
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.291
Teacher spread0.272 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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