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Record W1913748842 · doi:10.1063/1.4932317

Charge state breeding experiences and plans at TRIUMF

2015· article· en· W1913748842 on OpenAlexaff
F. Ames, M. Marchetto, Anders Mjøs, A. C. Morton

Bibliographic record

VenueReview of Scientific Instruments · 2015
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsElectron cyclotron resonanceIon sourceNuclear physicsPhysicsIonIon beamCyclotronBeam (structure)Nuclear engineeringAtomic physicsElectronPlasmaEngineering

Abstract

fetched live from OpenAlex

At the Isotope Separation and ACceleration (ISAC) facility at TRIUMF, an electron cyclotron resonance ion source (ECRIS) has been set up for the charge state breeding of radioactive ions. In order to reduce background from stable ions generated in the ECRIS, several measures, including changing materials for the plasma chamber and the surrounding components, have been implemented. Further reduction has been achieved by using the post-accelerator chain as a mass filter. Since the implementation of those measures in 2013, physics experiments with accelerated radioactive isotopes of Rb, Sr, K, and Mg have been performed. In most cases, a charge breeding efficiency of several percent has been achieved. With the planned expansion of the isotope production capabilities at TRIUMF within the Advanced Rare IsotopE Laboratory project, two new target stations, one using photo-fission induced by a high-power electron beam at 50 MeV and the other one using 480 MeV protons as at ISAC, will be put into operation within the next 5 yr. Additionally, a new electron beam ion source (EBIS) based charge state breeding system will be installed. Background from such a source is expected to be much lower. The drawback is that for the efficient operation of such a system, pulsed beam operation is required, which makes the installation of an additional ion buncher in front of the EBIS necessary.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.033
GPT teacher head0.260
Teacher spread0.227 · 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

Citations12
Published2015
Admission routes1
Has abstractyes

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