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Record W2066997250 · doi:10.1063/1.1429778

Charge state breeding applications with the ECR PHOENIX source: From low to high current production

2002· article· en· W2066997250 on OpenAlexafffund
T. Lamy, J.-L. Bouly, J.-C. Curdy, R. Geller, A. Lacoste, Patrick Solé, P. Sortais, T. Thuillier, J.L. Vieux-Rochaz, K. Jayamanna, M. Olivo, P. W. Schmor, D. Yuan

Bibliographic record

VenueReview of Scientific Instruments · 2002
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
FundersEuropean CommissionTRIUMF
KeywordsIon sourceAtomic physicsIon beamIonCyclotronThermal emittanceBeam (structure)Linear particle acceleratorMaterials scienceParticle acceleratorElectron cyclotron resonanceBeam emittanceIonizationIon beam depositionNuclear physicsElectronPhysicsPlasmaOptics

Abstract

fetched live from OpenAlex

The electron cyclotron resonance (ECR) charge state breeding method based on the PHOENIX source is first dedicated to the continuous high charge state radioactive ion production for cyclotrons, due to their q/m requirements, and to the high charge state production efficiency. It can be used as an injector for RFQ, linacs, and synchrotrons either in cw or pulsed operation. The efficiency of the 1+ to the n+ ion production and the charge breeding time are the fundamental parameters of the method, their dependence with regard to the 1+ ion beam emittance injected has been measured and will be discussed with regard to the radioactive ion beam acceleration. The efficiency of the process slightly decreases when injecting ion beam emittances higher than 30 π mm mrad, and remains constant in the 1+ radioactive intensity range available today and in the future. The ECR ion trap tuning associated with the afterglow mode permits the ionization, the accumulation, and the extraction of the injected primary beam keeping interesting efficiencies suitable to pulsed accelerators.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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

Citations35
Published2002
Admission routes2
Has abstractyes

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