Effects of Cocoa Butter Origin, Tempering Procedure, and Structure on Oil Migration Kinetics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The effects of cocoa butter (CB) origin, tempering procedure, and structure on oil migration kinetics were studied using a flatbed scanner followed by image processing and analysis. The migration rate (OMR) and migration distance ( I 10 ) of stained oil were determined in tempered and nontempered CBs. Tempered matrices had 10 to 50 times lower OMRs than nontempered CBs. In addition, the lag phase observed before significant oil migration was also significantly longer in tempered CBs (12 days vs 2 days in nontempered butters). Moreover, cocoa butter origin had a strong effect on OMR. Brazilian and Nigerian CBs had the highest OMR in both tempered and nontempered samples. Malaysian CB had the third highest OMR, but this effect was only significant in untempered samples. Finally, the lowest OMRs were found in Chinese, Ecuadorian, and Ivorian cocoa butters. The amount of oleic acid and triunsaturated triglycerides (UUU) was strongly correlated to OMR (the higher the UUU concentration, the lower the resistance to oil migration). However, the relationships between the permeability coefficients and structural factors (squared averaged particle size and crystalline domain size) suggest that the micro- and nanostructure of the material also plays a significant role in the oil migration process.
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.
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 it