ATLAS ITk Strip Sensor Quality Assurance Tests and Results of ATLAS18 Pre-production Sensors
Bibliographic record
Abstract
Towards the high luminosity (HL) operation of the Large Hadron Collider (LHC), the inner tracking system of the ATLAS detector will be replaced by a fully silicon-based inner tracker (ITk).Its outer region consists of 17,888 n + -in-p silicon strip sensors.In order to confirm key properties of the production sensors as well as to establish a solid workflow of quality inspection and monitoring of the various sensor properties, about 5% of the total strip sensors were produced in 2020 as a preproduction run.As a quality assurance (QA) program, irradiation of dedicated QA test pieces was periodically performed.The fluences of proton, neutron and γ-ray irradiations were up to 1.6×10 15 1-MeV neutrons/cm 2 and 0.66 MGy, which are equivalent to the maximum expected radiation fluences at the HL-LHC operation with a safety factor of 1.5.Results from 154 QA test pieces demonstrated high quality of the strip sensors through the pre-production.Detailed understanding of post-irradiated strip sensors was acquired, and the procedures of irradiation and post-irradiation QA testing were fully established.Consequently, the 3.8-year project of the strip sensor production for the ATLAS ITk detector was initiated in July 2021.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".