Comparison of ultrasonic and pulsed NMR techniques for determination of solid fat content
Bibliographic record
Abstract
Abstract In this work an ultrasonic velocity technique was compared to direct pulsed NMR (pNMR) spectroscopy for the determination of the solid fat content (SFC) of anhydrous milk fat (AMF), cocoa butter (CB), and blends of AMF and CB with canola oil (CO) in the range 100 to 70% (w/w). In situ measurements of ultrasonic velocity were carried out during cooling (50–5°C) and heating (5–50°C) of the fat samples, and SFC values were calculated. The SFC were also determined simultaneously by pNMR. Peak melting temperatures determined by DSC were used as an indicator of the polymorphic state of the different fats and fat blends. Estimates of SFC obtained using pNMR and ultrasonic velocimetry did not agree. Our results suggested that ultrasonic velocity was highly dependent on the polymorphic state of the solid fat. Ultrasonic velocity in fat that contained crystals in a more stable polymorphic form was consistently higher than in fat that contained crystals in a less stable polymorphic modification. A high attenuation of the signal was observed in milkfat and CB at lower temperatures, particularly after sitting for 24 h. This high attenuation could be a product of scattering by crystallites or by microscopic air pockets formed upon solidification of the material, or it could be due to high ultrasonic absorption associated with phase transitions. This research highlights some of the problems associated with applying ultrasonics to the determination of SFC.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".