First in-beam demonstration of a hybrid LaBr<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si101.svg" display="inline" id="d1e1878"><mml:msub><mml:mrow/><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:math>/CeBr<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si101.svg" display="inline" id="d1e1886"><mml:msub><mml:mrow/><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:math>/BGO array to measure radiative capture resonance energies in an extended gas target using a novel time of flight technique
Bibliographic record
Abstract
We have deployed a new hybrid array of LaBr3, CeBr3, and BGO scintillators for detecting $\gamma$ rays at the DRAGON recoil separator at TRIUMF. The array was developed to improve $\gamma$-ray timing resolution over the existing BGO array. This allows the average position of resonant capture in an extended gas target to be determined with $\sim$15 mm precision or better, even with five or fewer detected capture events. This, in turn, allows determination of resonant capture energies with statistical uncertainties below ${\sim} 1\%$. Here we report the results of a first in-beam demonstration of the array, measuring the $E_{cm} = 0.4906(3)$ MeV resonance in the ${}^{23}\mathrm{Na}(p,\gamma){}^{24}\mathrm{Mg}$ reaction, focusing on the timing properties of the array and its anticipated performance in future experiments with radioactive beams.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".