Intelligent agent-based system using dissolved gas analysis to detect incipient faults in power transformers
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
Power transformers are considered capital investments in the infrastructure of every power system in the world. They are the heart of electric power distribution and transmission systems, and it is essential that they function properly. Because power transformers are critical to the reliable operation of every power grid, ways to extend their lives, prevent incipient electrical failures, and improve preventive maintenance policies have become increasingly important. As a result, the development of accurate monitoring and diagnosis systems has been under consideration for several years [1], [2]. Much work has been done in recent years to find ways of prolonging transformer life and reducing the cost of failure [3], [4]. Still, new methods for analyzing the condition of transformers are needed. In addition to technologies such as sensing and measuring devices, software architecture is playing an important role in the development of powertransformer monitoring and diagnostic systems. These systems are complex and should fulfill a number of requirements.
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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 | 0.001 | 0.003 |
| 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) | 0.000 | 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