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Record W1970034610 · doi:10.1063/1.1702111

H − cusp source development for 100 MeV compact cyclotron at China Institute of Atomic Energy

2004· article· en· W1970034610 on OpenAlexfundno aff
Tianjue Zhang, Zhenguo Li, Chengjie Chu, Longcheng Wu, Junqing Zhong, Chuanrong Jiao, Tao Ge, Gaofeng Pan, Fengping Guan

Bibliographic record

VenueReview of Scientific Instruments · 2004
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
FundersChina Institute of Atomic EnergyNational Natural Science Foundation of ChinaTRIUMF
KeywordsCyclotronThermal emittancePhysicsUpgradeBeam (structure)Nuclear physicsBeam emittanceAtomic physicsSpectrometerIon sourceTandem acceleratorPlasmaOptics

Abstract

fetched live from OpenAlex

As a part of the Upgrade Project of Beijing Tandem Accelerator Laboratory, a 100 MeV compact cyclotron was designed for the generation of high intensity proton beams. Due to the limit of acceptance by the cyclotron central region, a new H− cusp source was developed at China Institute of Atomic Energy. The design of this new source is based on TRIUMF’s experience. More than 10 mA of H− beam with a measured emittance of 0.65 π mm mrad are obtained at a voltage of 28 kV from an extraction hole of 11 mm in diameter. In this article, the structure of the source, the magnetic field configuration of the multicusp and virtual filter, the extraction optics, the test results, and future improvements 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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

Citations11
Published2004
Admission routes1
Has abstractyes

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