Move the Laser Spot, Not the DUT: Investigating the New Micro-mirror Capability and Challenges for Localizing SEE Sites on Large Modern ICs
Bibliographic record
Abstract
Small spot size laser testing for single-event effects has proven to be a particularly productive path to insights on the physics of charge collection and circuit response that are difficult or impossible to obtain through broad ion beam tests. As a result, there are a number of such laser facilities; for example, four of them were compared in 2012 [1], but a relatively new facility at the facility at the University of Saskatchewan offers a unique galvo-mirror, laser-spot scanning capability in addition to the usual micrometer-based DUT motion stage [2]. Operating in a fashion similar to LASIX eye surgery, fast pin-point redirection of the laser beam makes tractable (seconds, not hours or days) comprehensive scanning of a millimeter size field-of-view. Combined with auto-stepping the field-of-view, this new spot scanning capability opens up the possibility of comprehensively covering a large die and finding all SEE sites, including the rare, but important, ones such as SEFIs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".