The ECRIS charge state breeding project at TRIUMF
Bibliographic record
Abstract
The performance of charge state breeding with an electron cyclotron resonance (ECR) ion source intended to increase the charge state of online produced radioactive ions at the ISAC facility at TRIUMF has been investigated. A 14 GHz PHOENIX from PANTECHNIK has been setup on a test bench. Singly charged ions have been produced with several ion sources typical for the on-line operation and were injected into the charge breeder. The main purpose of the tests has been the optimization of the efficiency for the charge breeding into the desired charge state. Maximum efficiencies reached so far with the standard one step deceleration of the ions in front of the plasma are up to about 6% for noble gas ions and about 3.5% for alkalines. As ion optics simulations show, the acceptance can be increased by a two step deceleration. In order to meet the velocity acceptance of the accelerator at different A/q values a similar two gap acceleration system for the highly charged ions has been installed to allow the source to run at different voltages. For the further beam transport to the accelerator, cross sections for charge exchange of the highly charged ions with the residual gas have been determined.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".