Development of Formulations and Processes to Incorporate Wax Oleogels in Ice Cream
Why this work is in the frame
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Bibliographic record
Abstract
The objective of this study was to investigate the influence of emulsifiers, waxes, fat concentration, and processing conditions on the application of wax oleogel to replace solid fat content and create optimal fat structure in ice cream. Ice creams with 10% or 15% fat were formulated with rice bran wax (RBW), candelilla wax (CDW), or carnauba wax (CBW) oleogels, containing 10% wax and 90% high-oleic sunflower oil. The ice creams were produced using batch or continuous freezing processes. Transmission electron microscopy (TEM) and cryo-scanning electron microscopy were used to evaluate the microstructure of ice cream and the ultrastructure of oleogel droplets in ice cream mixes. Among the wax oleogels, RBW oleogel had the ability to form and sustain structure in 15% fat ice creams when glycerol monooleate (GMO) was used as the emulsifier. TEM images revealed that the high degree of fat structuring observed in GMO samples was associated with the RBW crystal morphology within the fat droplet, which was characterized by the growth of crystals at the outer edge of the droplet. Continuous freezing improved fat structuring compared to batch freezing. RBW oleogels established better structure compared to CDW or CBW oleogels. These results demonstrate that RBW oleogel has the potential to develop fat structure in ice cream in the presence of GMO and sufficiently high concentrations of oleogel.
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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 | 0.000 | 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 it