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Record W2922349413 · doi:10.1016/j.nima.2019.04.007

The ATLAS ITk strip detector system for the High Luminosity LHC upgrade

2019· article· en· W2922349413 on OpenAlexaff
John Stakely Keller

Bibliographic record

VenueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsCarleton University
FundersHorizon 2020Deutsches Elektronen-SynchrotronScience and Technology Facilities CouncilEuropean CommissionCERN
KeywordsLarge Hadron ColliderDetectorUpgradeAtlas (anatomy)PhysicsLuminosityATLAS experimentElectronicsParticle physicsNuclear physicsOpticsElectrical engineeringComputer scienceEngineeringAstronomyOperating system

Abstract

fetched live from OpenAlex

The ATLAS experiment at the Large Hadron Collider is currently preparing major detector upgrades to meet the requirements of the High Luminosity LHC (HL-LHC), scheduled to begin in 2026. With the radiation damage and high density of tracks expected at the HL-LHC, the current Inner Detector would be inoperable, and will instead be replaced by an all-silicon Inner Tracker (ITk). The ITk consists of two sub-systems: a pixel detector close to the beam pipe, and a strip detector at larger radii. This paper presents results from an extensive design and prototyping effort for the ITk strip detector, including studies of the sensors, electronics, and support structures. The performance of the detector has been validated through testbeams, simulations, and thermal and electrical prototypes. Plans for the forthcoming production phase are also 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)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.037
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0370.024

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 head0.038
GPT teacher head0.346
Teacher spread0.307 · 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
GenreMethods

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

Citations4
Published2019
Admission routes1
Has abstractyes

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Same venueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentSame topicParticle Detector Development and PerformanceFrench-language works237,207