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Record W2086435568 · doi:10.1088/1748-0221/6/08/p08006

A Monte Carlo study of the fluctuations in Xe electroluminescence yield: pure Xe vs Xe doped with CH<sub>4</sub>or CF<sub>4</sub>and planar vs cylindrical geometries

2011· article· en· W2086435568 on OpenAlexaff
J. Escada, T.H.V.T. Dias, F.P. Santos, P.J.B.M. Rachinhas, C.A.N. Conde, A.D. Stauffer

Bibliographic record

VenueJournal of Instrumentation · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsYork University
FundersFundação para a Ciência e a Tecnologia
KeywordsMonte Carlo methodElectronPhysicsAtomic physicsRADIUSXenonIonizationScintillationYield (engineering)Electric fieldMaterials scienceIonNuclear physicsOpticsDetector

Abstract

fetched live from OpenAlex

Monte Carlo simulation is used to investigate the fluctuations in the Xe proportional electroluminescence (EL) yield H (also known as secondary scintillation) produced by sub-ionization primary electrons drifting in the gas under appropriate electric fields, comparing pure Xe gas with Xe doped with CH4 or CF4. The work is modeled on gas detectors of the gas proportional-scintillation type, where amplification is achieved through the production of EL under a charge-multiplication free regime. The addition of the molecular gases to Xe reduces electron diffusion, a desirable effect in large size detectors where primary electrons drift across a long absorption/drift region. However, the presence of the molecules reduces H and increases its fluctuations. In the case of CF4, the effects are very strong due to significant electron attachment in the EL field range, ruling out CF4 as an acceptable additive. The addition of CH4 affects H and its fluctuations to a much lower extent, and CH4 concentrations lower than ~1% may be an appropriate choice. In addition, Monte Carlo calculations in pure Xe under cylindrical geometry in a regime below charge multiplication have shown that fluctuations in the EL yield H are an order of magnitude higher than for planar geometry. For both geometries, though, the fluctuations have a negligible effect on the energy resolution, and variations of the anode radius in cylindrical geometry or grid parallelism in planar geometry may be a more significant cause of concern.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.214
Teacher spread0.197 · 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 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

Citations16
Published2011
Admission routes1
Has abstractyes

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