Probing ABCStar Front-End Readout ASICs for the new ATLAS Inner Tracker
Bibliographic record
Abstract
The ABCStar is a front-end ASIC implemented in a commercial 130 nm CMOS process designed for readout of the ATLAS ITk Silicon Strip sensors for the HL-LHC at CERN. The analog and digital circuitry of over 330,000 ASICs needs to be thoroughly tested to ensure they can accurately process the high rate of collision data within the HL-LHC and last throughout the lifetime of the detector. There are two probing sites to test the ABCStar ASICs on wafers containing 470 devices – a dedicated probing station at Rutherford Appleton Laboratory (RAL) and a specialist wafer testing company in Canada collaborating with Carleton University – with half being tested at each site. Probing at these two sites has bridged the methodological, technical and semantic gap between research facilities and the semiconductor testing industry. We report on the performance of the final design of the ABCstar ASIC and on the cross-checks between the two probing sites that demonstrated 99.8% agreement on test results from pre-production.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".