Investigation of Field Failures of Power Systems: A Different Whisker Story
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
ABSTRACT Several years ago a client experienced higher than expected failures of power controllers for large disk drive systems. The visual failure mode was severe heating of high power switching transistors, sufficient to cause partial melting of the leads and burning of the package and printed circuit board surfaces. The initial challenge was to find physical evidence of the cause starting with the failure location. Through the investigation which lasted several months, we found no evidence for obvious suspect causes, such as internal component and PCB failure, or flux residues that could cause short-circuit by ionic migration and dendrites. The first significant clue was finding a short-circuited low power control transistor, caused by a metallic filament bridging the leads. The filament was removed and SEM analysis revealed it to be a zinc whisker. Since there were no sources of zinc in the component packages or circuit assembly, we started to look for an external source of zinc whiskers. The investigation led back to the customer data centers and this paper will describe the discovery process and findings, and the corrective actions implemented to reduce the likelihood of future failures.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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