Mass Transfer During Osmotic Dehydration of Chub Mackerel Cylinders in Ternary Solution
Bibliographic record
Abstract
<p>In the analysis, design and optimization of an osmotic dehydration process is important to know the kinetic of water loss and solutes gain. In this study, the mass transfer during osmotic dehydration of chub mackerel (<em>Scomber japonicus</em>) cylinders in ternary solution glycerol/salt/water was analyzed. The models of Zugarramurdi &amp; Lupín and Azuara were used to describe mass transfer and to estimate equilibrium values. The radial effective diffusion coefficient was estimated using the analytical solution of Fick's second law. Diffusion coefficients were determined for a finite cylinder, for an infinite cylinder considering only the first term of the series and considering higher order terms of the series. The profiles of water and solutes during the osmotic dehydration were calculated by using the estimated water and solutes diffusivities. According to the results obtained, using three terms in the analytical solution of the Fick's second law is appropriate to determine the diffusion coefficients. The diffusion coefficient for infinite cylinder were 2.63×10<sup>-6</sup>, 4.11×10<sup>-6</sup> and 4.25×10<sup>-6</sup> cm<sup>2</sup>/s for water loss, salt and glycerol gain respectively. For a finite cylinder these values were 2.30×10<sup>-6</sup>, 3.67×10<sup>-6</sup> and 3.78×10<sup>-6</sup> cm<sup>2</sup>/s respectively. All the models proposed were in agreement with experimental data for solutes gain ((0.967&lt;R<sup>2</sup><sub>adj</sub>&lt;0.986); (0.0016&lt;<em>RMSE</em>&lt;0.039) and (4.17&lt;<em>P</em>&lt;10.0)). The model based on the solution of Fick’s Law for an infinite cylinder with higher order terms was the best fit for water loss and solutes gain. The equilibrium values estimated with Azuara model agree with the experimental (0&lt;relative error&lt;9.8). Water and solute distributions as a function of time and location in the radial direction were plotted.</p>
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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.
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