Identification and recovery of ATLAS18 strip sensors with high surface static charge
Bibliographic record
Abstract
The new all-silicon Inner Tracker (ITk) is being constructed by the ATLAS collaboration to track charged particles produced at the High-Luminosity LHC. The outer portion of the ITk detector will include nearly 18,000 highly segmented and radiation hard silicon strip sensors (ATLAS18 design). Throughout the production of 22,000 sensors, the strip sensors are subjected to a comprehensive suite of mechanical and electrical tests as part of the Quality Control (QC) program. In a large fraction of the batches delivered to date, high surface electrostatic charge has been measured on both the sensors and the plastic sheets between which the sensors are packaged for shipping and handling rigidity. Aggregate data from across QC sites indicate a correlation between observed electrical failures and the sensor/plastic sheet charge build up. To mitigate these issues, the QC testing sites introduced recovery techniques involving UV light or flows of ionizing gas. Significant modifications to sensor handling procedures were made to prevent subsequent build up of static charge. This publication details a precise description of the issue, a variety of sensor recovery techniques, and trend analyses of sensors initially failing electrical tests (IV, strip scan, etc.).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".