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Record W7162010960 · doi:10.82308/16889

Development of a cosmic muon trigger system for the characterization of tracking detectors to be used in the ATLAS muon detector upgrade

2017· dissertation· en· W7162010960 on OpenAlexaboutno aff
Wei Wu

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsUpgradeAtlas (anatomy)MuonLarge Hadron ColliderTracking system

Abstract

fetched live from OpenAlex

Afin de mieux gérer la luminosité instantanée élevée du Grand Collisionneur de Hadrons au CERN et réduire le taux de faux événements muoniques, les détecteurs «New Small Wheel» (NSW) vont remplacer les actuelles premières stations dans les régions avant du spectromètre à muons d'ATLAS. Le groupe ATLAS Canada est impliqué dans la fabrication et les tests d'une composante importante du NSW : les «small strip thin gap chambers» (sTGC). Une des responsabilités du groupe ATLAS de McGill est de compléter les tests de qualité et des évaluations de performance pour les nouvelles unités sTGC. Pour accomplir cette tâche, un système de déclencheurs ainsi que des systèmes de gaz, de contrôle lent et d'acquisition de données sont construits dans notre laboratoire de l'Université McGill. Ce projet de maîtrise se concentre sur le système de déclencheurs. Il contient le travail effectué pour maximiser l'efficacité du système dans la détection de muons cosmiques et pour approfondir notre connaissance de la performance du système à l'aide de simulations.

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 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)0.001
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 score0.112
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.035
GPT teacher head0.281
Teacher spread0.246 · 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 teacher head, 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

Citations0
Published2017
Admission routes1
Has abstractyes

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