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Record W2063080193 · doi:10.1063/1.2165271

Charge state breeding of radioactive ions with an electron cyclotron resonance ion source at TRIUMF

2006· article· en· W2063080193 on OpenAlexaff
F. Ames, R. Baartman, P. Bricault, K. Jayamanna, M. McDonald, M. Olivo, P. W. Schmor, D. Yuan, T. Lamy

Bibliographic record

VenueReview of Scientific Instruments · 2006
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsIon sourceIonAtomic physicsElectron cyclotron resonanceNuclear physicsCyclotronPhysicsThermal emittanceRange (aeronautics)Materials scienceNuclear engineeringElectronBeam (structure)Plasma

Abstract

fetched live from OpenAlex

Efficient primary ion sources at ISOL facilities normally produce singly charged ions. This limits the usable mass range for postacceleration due to the A∕Q acceptance of the accelerator. At the ISAC facility at TRIUMF an A∕Q below 7 is desired to avoid further stripping. Thus, charge state breeding is necessary if higher masses are to be accelerated. A 14 GHz ECRIS “PHOENIX” booster has been chosen as a breeder. In order to investigate and optimize its performance under ISAC conditions it has been set up at a test bench equipped with a standard ISAC target-ion-source to produce singly charged ions. A series of measurements has been performed with the noble gases Ar, Kr, and Xe. Efficiencies of more than 6% in the maximum of the charge state distribution after mass separation have been obtained and the emittance of the extracted beam and breeding times have been measured. This article gives a status report on the ongoing measurements.

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 score0.999
Threshold uncertainty score0.006

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 communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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

Citations18
Published2006
Admission routes1
Has abstractyes

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