Effect of Solid Fat Content on Structure in Ice Creams Containing Palm Kernel Oil and High‐Oleic Sunflower Oil
Why this work is in the frame
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Bibliographic record
Abstract
UNLABELLED: The development of a structural fat network in ice cream as influenced by the solid:liquid fat ratio at the time of freezing/whipping was investigated. The solid fat content was varied with blends of a hard fraction of palm kernel oil (PKO) and high-oleic sunflower oil ranging from 40% to 100% PKO. Fat globule size and adsorbed protein levels in mix and overrun, fat destabilization, meltdown resistance, and air bubble size in ice cream were measured. It was found that blends comprising 60% to 80% solid fat produced the highest rates of fat destabilization that could be described as partial coalescence (as opposed to coalescence), lowest rates of meltdown, and smallest air bubble sizes. Lower levels of solid fat produced fat destabilization that was better characterized as coalescence, leading to loss of structural integrity, whereas higher levels of solid fat led to lower levels of fat network formation and thus also to reduced structural integrity. PRACTICAL APPLICATION: Blends of highly saturated palm kernel oil and monounsaturated high-oleic sunflower oil were used to modify the solid:liquid ratio of fat blends used for ice cream manufacture. Blends that contained 60% to 80% solid fat at freezing/whipping temperatures produced optimal structures leading to low rates of meltdown. This provides a useful reference for manufacturers to help in the selection of appropriate fat blends for nondairy-fat ice cream.
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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) | 0.000 | 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