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Record W2077713476 · doi:10.1088/0022-3727/43/6/065502

A Monte Carlo study of photoelectron extraction efficiency from CsI photocathodes into Xe–CH<sub>4</sub> and Ne–CH<sub>4</sub> mixtures

2010· article· en· W2077713476 on OpenAlexaff
J. Escada, T.H.V.T. Dias, P.J.B.M. Rachinhas, F.P. Santos, J. A. M. Lopes, L. Coelho, C.A.N. Conde, A D Stauffer

Bibliographic record

VenueJournal of Physics D Applied Physics · 2010
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsPhotocathodePhotoelectric effectMonte Carlo methodAtomic physicsAnalytical Chemistry (journal)Range (aeronautics)ChemistryElectronArgonMaterials sciencePhysicsNuclear physicsOptoelectronics

Abstract

fetched live from OpenAlex

The extraction efficiency f for the photoelectrons emitted from a CsI photocathode into gaseous Xe–CH4 and Ne–CH4 mixtures is investigated by Monte Carlo simulation. The results are compared with earlier calculations in Ar–CH4 mixtures and in the pure gases Xe, Ar, Ne and CH4. The calculations examine the dependence of f on the density-reduced electric field E/N in the 0.1–40 Td range, on the incident photon energy E ph in the 6.8–9.8 eV (183–127 nm) VUV range and on the mixture composition. Results calculated for irradiation of the photocathode with a Hg(Ar) lamp are compared with experimental measurements for this lamp. To test the electron scattering cross-sections used in the simulations, electron drift parameters in Xe, Ne and their mixtures with CH4 are also presented and compared with available experimental data.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.222
Teacher spread0.215 · 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 designSimulation or modeling
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

Citations22
Published2010
Admission routes1
Has abstractyes

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