Cellulose chemical markers relationship with insulating paper post-mortem investigations
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
Oil soluble chemical markers such as methanol, ethanol and 2-furaldehyde for assessing the condition of insulating paper still present many challenges for an accurate interpretation in real transformers. Indeed, many conceptual parameters such as design (shell vs. core) or type of cooling are needed for a more accurate interpretation of the data. Moreover, similarly to water, the measured marker concentrations in oil are temperature-dependent, i.e. an existing partition phenomenon between the oil and the solid insulation modify the solubility of the markers, thus changing their apparent concentrations in the oil. Consequently, to follow the real trend of these species during the transformer's service life, it is crucial to correct their concentrations at a specific temperature, as is done for the water content. Knowing these facts and in order to calibrate a predictive model, Hydro-Québec decided to access equipment when dismantled, which enables a large amount of paper to be sampled from different sections of the windings. This allows for a more accurate representation of the transformer paper conditions in relation to transformer design. The paper condition obtained by measuring the degree of polymerization in accordance with the presence of chemical markers is a valuable process. We believe that it is possible to better understand the behavior of the paper insulation and to assess markers concentration thresholds using the oil analysis. This article discusses the recent experience in this field with specific cases.
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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 | 0.001 |
| 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