Development and application of soy-protein films to reduce fat intake in deep-fried foods
Bibliographic record
Abstract
A soy protein film coating was developed and evaluated to reduce fat transfer in deep-fried foods during frying. Soy protein isolate solutions (10% SPI) with 0.05% gellan gum as plasticizer cooled after being held at 80 °C for 20 min provided suitable films. There was a significant fat reduction (55.12 (±6.03)%db) between fried uncoated and coated discs of doughnut mix. The same films were used on potato fries. Some panellists observed a slight difference between the coated and uncoated fries but many preferred the coated fries over the uncoated ones. Penetration test on potato fries showed no significant difference between the texture of coated (SPI with gellan gum) and the uncoated fried samples. A solution of 10% SPI with 0.05% gellan gum is recommended for coating foods to reduce fat intake during deep-fat frying. © 2000 Society of Chemical Industry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".