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Record W7052825418

sTGC Testing for ATLAS’ New Small Wheel at McGill University and CERN

2018· other· en· W7052825418 on OpenAlexfundaboutno aff

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2018
Typeother
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsnot available
FundersCERNMcGill University
KeywordsNucleofectionHyporeflexiaTSG101SubpoenaLiquationPretext
DOInot available

Abstract

fetched live from OpenAlex

ATLAS’ muon small wheel must be replaced to improve muon track reconstruction and the forward muon trigger as the LHC tends towards higher collision rates. New multi – wire proportional chambers, small strip thin gap chambers (sTGCs), are being created in five countries for the new small wheel [1]. In Canada, the final stage of STGC production is to test the chambers with cosmic muons at McGill University [2]. The laboratory infrastructure at McGill is almost ready to allow data collection from the sTGCs without an operator present, the final step being to complete a temperature control and monitoring infrastructure for the electronic readout boards of the sTGCs. After the chambers are tested at McGill, they are sent to CERN where they are further tested with muon beam from the Super Proton Synchrotron. Preliminary results on the efficiency of one of the prototype chambers are presented. This report gives an overview of sTGC testing for the muon new small wheel with a focus on work completed by the author as part of the Institute of Particle Physics (Canada) Fellowship and CERN Summer Student Programme from May – August, 2018.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.004

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 head0.227
Teacher spread0.193 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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