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Record W2121721855 · doi:10.1142/s1793626809000235

The Dielectric Wall Accelerator

2009· article· en· W2121721855 on OpenAlexfundno aff
George Caporaso, Yu-Jiuan Chen, S. Sampayan

Bibliographic record

VenueReviews of Accelerator Science and Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsnot available
FundersSLAC National Accelerator LaboratoryPartenariat Canadien Contre Le CancerLawrence Livermore National LaboratoryU.S. Department of Energy
KeywordsParticle acceleratorElectric fieldAccelerationNanosecondElectronBeam (structure)PhysicsPulse (music)Charged particleDielectricProtonOpticsDetectorIonNuclear physicsOptoelectronics

Abstract

fetched live from OpenAlex

Dielectric wall accelerators, a class of induction accelerators, employ a novel insulating beam tube to impress a longitudinal electric field on a bunch of charged particles. The surface flashover characteristics of this tube may permit the attainment of accelerating gradients on the order of 100 MV/m for accelerating pulses on the order of a nanosecond in duration. A virtual traveling wave of excitation along the tube is produced at any desired speed by controlling the timing of pulse-generating modules that supply a tangential electric field to the tube wall. Because of the ability to control the speed of this virtual wave, the accelerator is capable of handling any charge-to-mass-ratio particle; hence it can be used for electrons, protons and any ion. The accelerator architectures, key technologies and development challenges will be described.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.006

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 head0.009
GPT teacher head0.250
Teacher spread0.241 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations46
Published2009
Admission routes1
Has abstractyes

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Same venueReviews of Accelerator Science and TechnologySame topicElectrostatic Discharge in ElectronicsFrench-language works237,207