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
Bibliographic record
Abstract
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%).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".