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BETSEE: testing for system-wide effects of single event effects on ITk strip modules

2023· article· en· W4315706337 on OpenAlexaff
C. Bélanger-Champagne, J. R. Dandoy, B. J. Gallop, T. C. Gosart, C. M. Helling, P. Keener, K. Krizka, Bobby McGovern, G. A. Mullier, A. Poley, B. R. Roberts, C. Sawyer, A. Wall, H. Wang, M. Warren

Bibliographic record

VenueJournal of Instrumentation · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsSimon Fraser UniversityUniversity of British ColumbiaTRIUMF
FundersScience and Technology Facilities Council
KeywordsUpgradeDetectorLarge Hadron ColliderEvent (particle physics)Atlas (anatomy)Heavy ionApplication-specific integrated circuitComputer hardwarePhysicsComputer scienceChipBeam (structure)Embedded systemNuclear physicsIonOpticsOperating systemTelecommunications

Abstract

fetched live from OpenAlex

Abstract The Inner Tracker silicon strip detector (ITk Strip) is a part of the ATLAS upgrade for the HL-LHC. The detector readout and control is accomplished by the interaction of three on-module custom ASICs (ABCStarv1, HCCStarv1 and AMACstar). All ASICs are designed with protections against Single Event Errors. Their resilience at the system-level can be tested using the Board for Evaluation of Triple-chip Single Event Effects (BETSEE). This special board places all three ASICs into the beam-spot of a test beam facility concurrently and allows for module-like operation. The results from irradiating BETSEE with heavy ions and protons will be presented.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.017
GPT teacher head0.260
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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