Experiences and lessons learned from the End-of-Substructure card production of the ATLAS ITk Strip upgrade
Bibliographic record
Abstract
Abstract The silicon tracker of the ATLAS experiment will be upgraded for the upcoming High-Luminosity Upgrade of the LHC. The main building blocks of the new strip tracker are modules that consist of silicon sensors and hybrid PCBs hosting the read-out ASICs. The modules are mounted on rigid carbon-fiber substructures, known as staves in the central barrel region and petals in the end-cap regions, that provide common services to all the modules. At the end of each stave or petal side, a so-called End-of-Substructure (EoS) card facilitates the transfer of data, power, and control signals between the modules and the off-detector systems. The EoS connects up to 28 data lines to one or two lpGBT chips that provide data serialization and uses a 10 Gbit s-1 versatile optical link to transmit signals to the off-detector systems. To meet the tight integration requirements in the detector, several different EoS card designs are needed. The power to the EoS is provided by a dedicated dual-stage DC-DC package providing 2.5 V and 1.2 V to the EoS cards. As the EoS production of almost 2000 EoS cards and accompanying DC-DC converters is getting close to completion, the production experience including detailed QC statistics and design validation (QA) results is reported on.
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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 | 0.016 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".