Mass Transfer Behavior of Plant Tissues During Osmotic Dehydration
Bibliographic record
Abstract
Biological structures and behavior of biomaterials are difficult to describe in quantitative terms. In a process such as osmotic dehydration of plant tissues, these complex structures pose a challenging factor in the optimization process and design of equipment. The structure and properties of the tissues affect the mass transfer phenomena occurring in plant tissues during osmotic dehydration. The purpose of this study was to develop a method to classify the mass transfer behavior of different plant materials during osmotic dehydration. The method of classification was based on the description of the material behavior according to easily measurable parameters. These parameters were water loss and solids gain. By fitting an inverse polynomial model to the kinetics data, rates and fluxes of mass transfer were calculated. Two methods of classification were developed based on the rates and fluxes of mass transfer. The method based on fluxes accommodated for the different geometries of the samples. The two methods were combined to calculate the value of, which is the ratio of the bulk flow transport to diffusion transport at the interface of the solution at time 0. The seven kinds of fresh fruit materials that were analyzed were divided into three classes. Their mass transfer behaviors were then described in quantitative terms as either “fast”, “average” or “slow”. These methods of classification have provided description of the behavior of various plant tissues during osmotic dehydration.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".