Relationships between molecular structure and kinetic and thermodynamic controls in lipid systems. Part I: propensity for oil loss of saturated triacylglycerols
Bibliographic record
Abstract
Pure saturated triacylglycerols (TAGs) in canola oil were used as model systems to analyse oil loss in structured oil both from thermodynamic and kinetic perspectives. Two important parameters which effectively and predictively measure the relative propensity of a solid network to lose/hold oil were defined: (1) the rate of oil loss, K, which is a quantified representation of the kinetics of oil loss and (2) the initial amount of oil susceptible to be lost, i.e., the propensity for oil loss (POL), which is a representation of the thermodynamics of oil binding. It was found that the POL and K values do not always trend in the same fashion, suggesting that the mechanism of oil binding is complex, depending on the structurant's crystalline form locked within the oil network. The two parameters were, however, correlated to the melting and thermal behavior of the structurants, to the polymorphic structures that are obtained during the cooling process and to the habit (shape, size and morphology) of the crystalline phase in the oil. Both POL and K had a strong correlation to the oil loss.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".