Field-aged cable material diagnosis by thermally stimulated currents
Bibliographic record
Abstract
The Thermally Stimulated Currents (TSC) technique has been studied as a method for detecting dry state water trees in field-aged cables. Measurements were taken on medium voltage extruded cable samples of crosslinked polyethylene (XLPE). Samples were peeled-off from several well characterized field-aged and one unaged cables. Insulating material has been characterized with regard to water-tree density. TSC peaks were observed around -30/spl deg/C (/spl beta/) and 110/spl deg/C (/spl alpha/) for field-aged and unaged insulation. Low-temperature peak intensity variations throughout cable radii have been observed and assumed to be related to the cable insulation characteristics. No correlation has been observed between the total integrated charge from /spl beta/ peak integration and the dry state water-tree surface density of the samples. In addition, TSC and TSPC (Thermally Stimulated Polarization Currents) measurements on treed and untreed regions of the same cable at the same radius have been carried out in order to compare samples having the same characteristics except for the presence of dry state water trees. Variations in /spl alpha/ peak intensity was related to the lower water-tree resistivity even in the dry state.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".