Characterization of isotherms and thin-layer drying of red kidney beans, Part I: Choosing appropriate empirical and semitheoretical models
Why this work is in the frame
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Bibliographic record
Abstract
Desorption and adsorption isotherms and drying characteristics of red kidney beans were studied using static and dynamic methods, respectively. The desorption and adsorption isotherms were determined at 60, 50, 40, 30, 20, and 10°C with 32–91% relative humidity (RH). The constant RHs were generated using six saturated salt solutions at constant temperatures. The drying characteristics were determined using a thin-layer dryer with drying air at 50, 40, and 30°C with 35 and 50% RH. The dimensions of the kidney beans before and after drying were measured and shrinkage and sphericity of the beans were calculated. A new method to evaluate the best-fitted equation to characterize the thin-layer drying data was developed. The best-fitted equations to describe the desorption and adsorption isotherms were the modified Chung–Pfost and modified Guggenheim–Anderson–deBoer. The red kidney beans only experienced a falling rate drying period and had a largest shrinkage in the length direction during drying. The Henderson and Pabis model and the modified Page model were the best-fitted models to describe the thin-layer drying data. Using only the values of R2 and mean squared error to evaluate the semitheoretical and empirical models might not be enough. The method developed in this study could help develop a semitheoretical or empirical model with a higher accuracy of drying constant, which could be used to estimate the effective water diffusivity.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 it