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

2023· article· en· W4315706337 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.375
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

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

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