Changes in the calcium cluster distribution of ultrafiltered and diafiltered fresh skim milk as observed by Small Angle Neutron Scattering
Bibliographic record
Abstract
The effect of ultrafiltration and diafiltration on the distribution of the calcium phosphate clusters of the casein micelle was investigated using Small Angle Neutron Scattering (SANS). In the case of ultrafiltration, fresh skim milk was subjected to concentration using membrane filtration up to 5× its original volume, the retentate was rediluted with its corresponding serum and subsequently dialyzed against reconstituted milk powder dispersed in D2O/H2O (UF 5×(D)). In the case of diafiltered samples, the samples were concentrated adding water (diafiltration) at two different levels (DF 2·5× or DF 5×) and then redispersed with D2O/H2O. In the DF 5× case, the serum components were diluted to less than 1% of their original concentration. For analysis, all samples had the same volume fraction of dispersed casein micelles (φ=0·1), which is that of the control, unprocessed skim milk. A peak in the SANS data was observed in fresh skim milk at a scattering vector, qo, of 0·034 Å-1 (directly proportional to the reciprocal characteristic length), in agreement with previous literature results. Neutron data on the ultrafiltered, UF 5×(D) and diafiltered, DF 2·5× and DF 5× milk samples showed a progressive decrease in the intensity of the peak but invariance in qo. These results, combined with the determination of soluble and insoluble calcium in the samples, suggest a progressive and irreversible removal of calcium from within the micelle during membrane filtration of milk. Using SANS it was possible to clearly show changes in the micellar calcium clusters that may not otherwise be fully determined by only measuring the amount of total and insoluble calcium in milk.
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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 | 0.001 |
| 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".