ECRIS operation and developments at TRIUMF
Bibliographic record
Abstract
Rare isotope beams are used at the ISAC facility at TRIUMF for studies mainly in nuclear and astrophysics, but also for applications ranging from material science to medicine. The isotopes are produced via the ISOL technique and ionized via a set of different ion sources depending on the application. In cases where highly charged ions are needed, charge state breeding is done with a 14.5 GHz PHOENIX ECR ion source from PANTECHNIK. The source has been operational for more than a decade providing a wide range of ions from Na to U at A/Q 7 for post-acceleration. A second ECR ion source, a SUPERNANOGAN also from PANTECHNIK is used to provide highly charged ions from stable isotopes either for set-up and calibration for the rare isotope beams or for nuclear reaction studies with stable ions. The presentation will give a summary of results and will describe the challenges and improvements to the original sources. For the charge state breeding this is mainly increasing the efficiency and the purity of the delivered beams. In the case of the SUPERNANOGAN special emphasis is put on operational aspects to cover a wide range of elements and easy switchover. The latest in this series of improvements is the implementation of two frequency plasma heating in both ion sources.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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".