Effects of Crystalline Microstructure on Oil Migration in a Semisolid Fat Matrix
Bibliographic record
Abstract
Oil migration from a 60:40 (w/w) mixture of peanut oil and chemically interesterified and hydrogenated palm oil (IHPO) was a strong function of the cooling rate experienced by the fat mixture during crystallization, namely, 0.4, 1.2, and 6.0 °C/min. The relative oil loss determined gravimetrically was inversely proportional to the cooling rate. Oil loss was also inversely related to the storage modulus (G‘) and the yield force of the fat. After 1 day storage at 20 °C, the start of the oil loss studies, the composition and polymorphism of the fat crystals crystallized at different rates were similar, as judged by differential scanning calorimetry and powder X-ray diffraction. Crystals were in the same β‘ modification and had similar peak melting temperatures. Microstructure, on the other hand, was profoundly affected by the cooling rate: average crystal size decreased from 8.2 μm (at 0.4 °C/min) to 3.9 μm (at 6.0 °C/min). Using Darcy's Law, it was possible to calculate permeability coefficients using the structural parameters obtained in this work. Decreases in permeability coefficient as a function of increasing cooling rate were mainly related to decreases in crystal size.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".