Development of a Process for Color Improvement of Low-Grade Dark Maple Syrup by Adsorption on Activated Carbon
Bibliographic record
Abstract
Low-grade dark maple syrup was successfully discolored on activated carbon. Several experimental parameters were tested, namely, the mixing time (20, 40, and 60 min), concentration of the activated carbon (0.1, 0.3, and 0.5 g/100 mL), type of activated carbon (I, II, and III), activated carbon particle size (25, 50, and 75 μm), stirring speed (200, 400, and 600 rpm), and temperature (40, 60, and 80 °C). The obtained results showed that the discoloration is optimal by applying the following parameters: a mixing time of 40 min with a type III activated carbon at a concentration of 0.3 g/100 mL. These parameters yielded a light transmittance at 560 nm of 83.70 ± 0.21%, which ranks the syrup in the extra clear class according to the Canadian classification. The results showed that among the tested carbons, the adsorption on the type III carbon followed the Langmuir, Freundlich, and Langmuir-Freundlich adsorption isotherms. Regarding the effect of the particle size, the obtained results showed that a mean size of 25 μm combined with a stirring speed of 200 rpm and working temperature of 80 °C was the most effective one. The optimized conditions showed a good adequacy with the Langmuir and Freundlich models. The discoloration process by using the type III activated carbon followed the pseudo-second-order kinetics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".