High precision measurement of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mmultiscripts><mml:mi mathvariant="normal">Ne</mml:mi><mml:mprescripts/><mml:none/><mml:mn>19</mml:mn></mml:mmultiscripts><mml:mspace width="4pt"/><mml:mi>β</mml:mi></mml:math>-decay half-life using real-time digital acquisition
Bibliographic record
Abstract
The half-life of $^{19}\mathrm{Ne}$ was measured using a real-time digital multiparametric acquisition system, providing an accurate time stamp and relevant information on the detector signals for each decay event. An exhaustive offline analysis of the data gave unique access to experimental effects potentially biasing the measurement. After establishing the influence factors impacting the measurement such as after-pulses, pile-up, gain, and baseline fluctuations, their effects were accurately estimated and the event selection optimized. The resulting half-life, $17.2569\ifmmode\pm\else\textpm\fi{}0.{0019}_{(\text{stat})}\ifmmode\pm\else\textpm\fi{}0.{0009}_{(\text{syst})}$ s, is the most precise up to now for $^{19}\mathrm{Ne}$. It is found to be in agreement with two recent precise measurements and not consistent with the most recent one [L. J. Broussard et al., Phys. Rev. Lett. 112, 212301 (2014)] by 3.0 standard deviations. The full potential of the technique for nuclei with half-lives of a few seconds is discussed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".