Pre-production results from ATLAS ITk Strip Sensors Quality Assurance Testchip
Bibliographic record
Abstract
Abstract The production of strip sensors within the framework of the ATLAS Inner Tracker (ITk) development is a process which requires continuous evaluation during the full production period (about 4 years). Such an evaluation is divided into two different parts: Quality Control (QC), which focuses on the final product (the actual sensors) and tries to identify possible defects once the fabrication is completed, and Quality Assurance (QA), which aims to prevent deviations in the manufacturing process and uses specifically-designed test structures. The initial sensor pre-production consists of 5% (1041 sensors) of the total number of sensors expected during production. As part of pre-production, the collaboration has measured key parameters from miniature strip sensors (minis), monitor diodes (MD8), and the ATLAS Testchip, before and after irradiation. In this contribution we focus on the analysis of the results of the MD8 and the Testchip. All parameters have been obtained from the test structures (MD8, bias resistors, interdigitated structures, field oxide capacitors, coupling capacitors, punch-through protection structures and cross-bridge resistors) measured at the different test sites (KEK/Tsukuba, Birmingham, Toronto, Ljubljana, Valencia, Carleton, Prague, CNM-Barcelona). The results are compared to predefined pre- and post-irradiation specifications for each tested parameter.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".