Deep Fat Frying Of Foods—Transport Phenomena
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Many theoretical and experimental studies have been conducted to understand the mechanisms of heat and mass transfer during deep fat frying. This, in turn, has helped in understanding transport phenomena during frying and the relationships between thermal and physical properties of the products and the frying media. Most of the studies have focused on the determination of convective heat transfer coefficient and mechanisms of moisture and oil transfer. Mathematical models also have been developed to describe and predict the process. Many studies have adopted the assumptions used for the drying process for simplification. Recently, more realistic and sophisticated models have been introduced. Keywords: Deep fat fryingHeat transferMoisture lossOil uptakeModeling The authors gratefully acknowledge NSERC (Natural Science and Engineering Research Council of Canada) for research funding.
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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 | 0.001 | 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) | 0.011 | 0.001 |
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