Correlation of tangible quality parameters of vegetable-based transformer fluids
Bibliographic record
Abstract
Due to the inherent environmental footprint of petroleum derived transformer fluids, the power industry is gradually exploring the potential of vegetable oils as alternatives. The impetus comes mostly from vegetable oils renewability and their inherent biodegradability. However, the major drawback in the use of vegetable oils as dielectric fluids is their lower oxidative stability and higher kinematic viscosity compared to mineral oils. The results obtained clearly demonstrate the correlation between spectroscopic data induction time, kinematic viscosity, acid value, and peroxide value. Quantitatively, the absorption frequencies of functional groups in vegetable oil transformer fluids that can be correlated to the mentioned quality parameters show noticeable changes with aging/oxidative degradation. The study also demonstrates the utility of integrating spectroscopic data to understand trends in induction time and kinematic viscosity of oil samples heated under transformer service conditions.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".