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Record W2774701019 · doi:10.82308/5021

Studies of cosmic ray events in ATLAS sTGC muon chamber prototypes

2018· article· en· W2774701019 on OpenAlexaboutno aff
Felix Leger

Bibliographic record

VenueOpen MIND · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCosmic rayAtlas (anatomy)MuonPhysicsBubble chamberCOSMIC cancer databaseNuclear physicsAstronomyGeology

Abstract

fetched live from OpenAlex

Four years after its first long shutdown in 2015, the Large Hadron Collider (LHC) will be shut down once more for a luminosity upgrade. During that time, the ATLAS detector on the LHC ring will also follow an upgrade program, one upgrade being the replacement of the Small Muon Wheels New Small Muon Wheels containing small-strip Thin Gap Chambers (sTGCs). The sTGCs built in Canada will be tested at McGill University before their installation in ATLAS. A testing facility has been constructed and a 40 x 60 cm^2 sTGC prototype has been used to deliver preliminary measurements from cosmic rays. This thesis will present the development of a robust tracking algorithm which can handle extra clusters and multiple tracks in an sTGC detector. This algorithm also categorizes events based on their number of clusters and tracks. By modifying the trigger time window of the sTGC prototype, the evolution of the distribution of events over this categorization is shown.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score1.000

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)0.0010.000

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 head0.056
GPT teacher head0.345
Teacher spread0.289 · 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.

Study designObservational
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
Published2018
Admission routes1
Has abstractyes

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