Effects of food gums and pre‐drying on fat content of fabricated fried chips
Bibliographic record
Abstract
Summary Deep‐frying contributes to the unique taste and texture of fried products. However, they are low in nutritional value. Food industries actively trying to find ways to reduce the fat content while maintaining organoleptic properties of fried foods. In this work, effects of pre‐drying and adding food gums on the moisture and fat contents of chips were evaluated. The chips were pre‐dried for 60 and 90 min, and gellan gum, guar gum, methylcellulose and xanthan gum were added at the concentration of 0.25, 0.75, 1 and 2 % w/w. The xanthan gum was the most effective gum for fat reduction. The addition of 0.25 % w/w xanthan gum and at 90 min pre‐drying reduced the fat content from 20 % (control) to 15 % w/w. The results also indicated that the reduction of moisture content after frying was not affected by the type of gums but the method of pre‐drying.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".