Cocoa butter equivalent from Kpangnan butter and Pequi oil
Bibliographic record
Abstract
Novel cocoa butter equivalents were designed using dry fractionated Pequi oil and solvent fractionated Kpangnan butter. Static crystallization of binary mixtures of these two fractions into the triclinic form (β2) was achieved after 12 days for all mixtures and after 4 days for the 80:20 w/w and 90:10 w/w fractionated Kpangnan:Pequi oil mixtures. Moreover, after 60 days of storage at 22oC, all binary blends (except 100% fractionated pequi oil and 100% fractionated Kpangnan butter) were crystallized in the most stable triclinic crystal form (β1). Here we also discovered an unusual melting behavior for the fractionaled 30:70 w/w and 20:80 w/w fractionated Kpangnan:Pequi oil mixtures, where after 4 days of static crystallization at room 22oC, these mixtures displayed higher than predicted melting points, 41.89 oC and 33.32 oC, respectively. This suggested a faster kinetics of transformation to the triclinic β2 form for those mixtures. Our results suggest that the 30:70 w/w fractionated Kpangnan:Pequi oil mixture with a melting point of 34oC after 60 days storage at 22oC, a stable triclinic β2 form, and a triglyceride composition of 28% POP, 4.6% POS and 33% SOS displayed solid state characteristics, melting point and crystal structure, of a commercial cocoa butter equivalent.
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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 | 0.000 |
| 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".