Bibliographic record
Abstract
This study analyzed SEU measurements made of the ESA Monitor at GSI, RADEF, UCL, and TAMU. An IRPP model was implemented through the use of FLUKA that was calibrated to the measurements of ions above the LET threshold. The model proved successful in reproducing proton measurements that are entirely independent of the calibration. When applied to the sub-threshold region, experimental measurements were underestimated by a factor of $\sim$3 for the high energy ions at GSI, a factor of $\sim$10 for the ions at UCL/RADEF, and an anomalous factor of $\sim$300 for the ion at TAMU. Several possible sources of systematic uncertainty were investigated including sensitive volume size, BEOL thickness, and substrate thickness. Additionally, the impact of including air between the beam and the DUT as well as side effects due to the simulated geometry were explored. It was found that none of these sources can provide a substantial enough impact on the SEU cross-section to reconcile the anomalous measurement made at TAMU.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".