Effects of Canola Oil Dilution on Anhydrous Milk Fat Crystallization and Fractionation Behavior
Bibliographic record
Abstract
Blends of anhydrous milk fat (AMF) and canola oil (CO) were cooled from 35 to 5 degrees C at 0.1 degrees C/min, held for 24 h, and centrifuged to separate the liquid and crystalline fractions. The blends' crystallization behaviors and microstructures depended on the level of CO present. Onset and half times of crystallization reflected a slower crystallization mechanism at higher levels of CO dilution. These differences were accompanied by a change in microstructure from large spherulites to smaller particles. The biggest change occurred between the 1:4 and 1:5 blends. Canola oil dilution also influenced the polymorphism of milk fat. Whereas only the beta' polymorph was observed in the crystallized 1:2 blend, the beta polymorph predominated in the 1:8 blend. Some solubilization of AMF solids into CO was observed. This increased gradually with increasing CO concentration. Compositional analysis revealed the exchange of AMF and CO species between the liquid and crystalline fractions. The crystalline fractions were slightly enriched in AMF triacylglycerols, particularly with the more dilute blends (1:7 and 1:8). Large amounts of oil were trapped in the crystalline fractions, particularly for the concentrated AMF:CO blends where the beta' crystals and spherulitic microstructures were observed. Although the solid fat content profiles of the fractionated blends were marginally higher than those of the starting blends, the samples were very soft and oily. This strategy of using CO to fractionate milk fat was limited by the poor separation of solids and liquid during centrifugation.
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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 | 0.000 |
| 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 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".