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Recent Improvements in Beam Delivery with the TRIUMF’s 500 MeV Cyclotron

2017· article· en· W2611530126 on OpenAlexaff
Iouri Bylinskii, R. Baartman, K. Jayamanna, Thomas Planche, Yi‐Nong Rao

Bibliographic record

VenueJACOW · 2017
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsCyclotronNuclear physicsPhysicsBeam (structure)OpticsPlasma

Abstract

fetched live from OpenAlex

TRIUMF’s 500 MeV H⁻ Cyclotron, despite its 44 years age is under continuous development. Many aspects of beam delivery have been improved over the last few years. Regular 3-week cusp source filament exchange cycle has advanced to multi-months due to greatly improved filament life time. Fine source tuning allowed beam intensity rise in support of routine extraction of 300 uA of protons. The injection line model has been fully correlated with online measurements that enabled its tuning and matching to the emittance defining slits and the cyclotron entrance. Cyclotron routinely produces 3 simultaneous high intensity beams (~100 uA each). Multiple techniques have been developed to maintain extracted beams intensity stability within ± 1%. Record extraction foil life times in excess of 500 mA-hours have been demonstrated with highly-oriented pyrolytic graphite foil material and improvements in foil holder. Beam rastering on ISOL target allowed higher yields. A single user extraction at 100 MeV was achieved by applying phase slip and deceleration inside the cyclotron.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.016

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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