Improved measurement of the<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>2</mml:mn><mml:mi>ν</mml:mi><mml:mi>β</mml:mi><mml:mi>β</mml:mi></mml:mrow></mml:math>half-life of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow/><mml:mn>136</mml:mn></mml:msup></mml:math>Xe with the EXO-200 detector
Bibliographic record
Abstract
We report on an improved measurement of the $2\ensuremath{\nu}\ensuremath{\beta}\ensuremath{\beta}$ half-life of ${}^{136}$Xe performed by EXO-200. The use of a large and homogeneous time-projection chamber allows for the precise estimate of the fiducial mass used for the measurement, resulting in a small systematic uncertainty. We also discuss in detail the data-analysis methods used for double-$\ensuremath{\beta}$ decay searches with EXO-200, while emphasizing those directly related to the present measurement. The ${}^{136}$Xe $2\ensuremath{\nu}\ensuremath{\beta}\ensuremath{\beta}$ half-life is found to be ${T}_{1/2}^{2\ensuremath{\nu}\ensuremath{\beta}\ensuremath{\beta}}$ = $2.165\ifmmode\pm\else\textpm\fi{}0.016(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}0.059(\mathrm{sys})\ifmmode\times\else\texttimes\fi{}{10}^{21}$ yr. This is the most precisely measured half-life of any $2\ensuremath{\nu}\ensuremath{\beta}\ensuremath{\beta}$ decay to date.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".