Algal meal supplementation of the cows' diet alters the physical properties of milk fat
Bibliographic record
Abstract
A three-week algal meal supplementation of the cows' basal diet resulted in an increase in the firmness of milk fat crystallized isothermally at 5 degrees C for 24 h--the apparent elastic constant increased from 100 to 224 N/mm. This was accompanied by a decrease in solid fat content, from 47.7% to 44.4%. The crystallization behaviour of milk fat was also modified significantly. The rate constant of crystallization (Avrami constant) of the enriched milk fat at 19 degrees C was approximatly 20 times higher than that of control milk fat. A shorter induction time of nucleation was also observed in the temperature range [20, 27 degrees C]. These effects were attributed to a higher degree of supersaturation of the enriched milk fat. Enriched milk fat nucleated in a more stable beta' polymorphic form at 5 degrees C, while control milk fat nucleated in the metastable alpha form, as determined by powder X-ray diffraction and differential scanning calorimetry. Changes in the microstructure of the material were observed by polarized light microscopy at 5 degrees C. The enriched milk fat displayed a greater amount of crystal clustering than the control. This effect was reflected in a decrease in the box-counting mass fractal dimension (Db) of the fat crystal network from 1.853 to 1.809. The decrease in Db closely predicted the observed 2.2-fold increase in the elastic constant of the fat. These changes in mechanical properties, crystallization behaviour and microstructure were driven by an increase in the 18:1 trans and a decrease in the 18:1 cis fatty acid content of the enriched milk fat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".