Preliminary studies on Improving the Properties of Canola Oil by Addition of Methyl Ester from a Saturated Vegetable Oil
Bibliographic record
Abstract
Vegetable oils have excellent dielectric properties and high thermal characteristics (flash point and fire point). However, their general acceptability is questionable due to the poor viscosity profile at low temperatures and oxidation stability. Thus, enhancement of the oxidation stability and flow properties of canola oil-based dielectric liquid stands as the main goal of the present study. Methyl ester synthesized from palm kernel oil was mixed with a commercially available canola-based insulating liquid in 25%, 50%, and 75% concentrations. The behavior of all samples was monitored during accelerated thermal aging in the presence of oxygen for different periods. Specifically, observations were made for fresh samples under ambient temperature and 12, 24, 36, and 48 hours at $110^{\circ}\mathrm{C}$. Acidity, moisture, and dissolved decay particles were used as a factor for monitoring the rate of degradation. It was observed that the mixture with a high percentage of methyl ester (C and D) shows stability to oxidation. This experimental investigation shows that a mixture of oil with saturated and unsaturated fatty acids has promising thermo-oxidation stability properties.
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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".