Development of a Low-Cost Diagnostic Tool to Assess the Sufficiency of Food Drying Processes in Developing Countries
Bibliographic record
Abstract
Food drying reduces moisture content supporting microbial growth that contributes to food spoilage in developing countries. However, there is a lack of efficient low-cost tools to assess the sufficiency of food drying in small-scale operations in developing countries. Thus, a model was developed using a thermal imaging process to determine the moisture content of dried Royal Gala apples based on their cooling rate. Fitted regression curves showing absolute temperature versus cooling time were plotted for different wet basis moisture contents. The regression curve obtained for a safe range of moisture (9-11%) produced an equation with a higher constant and exponent than the curve for a potentially unsafe range (15-17%), showing the potential of this method. Further analysis is needed to evaluate the applicability of this method in other types of dried foods and conditions, as well as to explore the possibility to use the developed model in a mobile application.
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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".