Experimental study of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mmultiscripts><mml:mi mathvariant="normal">C</mml:mi><mml:mprescripts/><mml:none/><mml:mn>13</mml:mn></mml:mmultiscripts><mml:mo>(</mml:mo><mml:mi>α</mml:mi><mml:mo>,</mml:mo><mml:mi>n</mml:mi><mml:mo>)</mml:mo><mml:mmultiscripts><mml:mi mathvariant="normal">O</mml:mi><mml:mprescripts/><mml:none/><mml:mn>16</mml:mn></mml:mmultiscripts></mml:mrow></mml:math> reactions in the Majorana Demonstrator calibration data
Bibliographic record
Abstract
Neutron captures and delayed decays of reaction products are common sources of backgrounds in ultrarare event searches. In this work, we studied $^{13}\mathrm{C}(\ensuremath{\alpha},n)^{16}\mathrm{O}$ reactions induced by $\ensuremath{\alpha}$ particles emitted within the calibration sources of the Majorana Demonstrator. These sources are thorium-based calibration standards enclosed in carbon-rich materials. The reaction rate was estimated by using the 6129-keV $\ensuremath{\gamma}$ rays emitted from the excited $^{16}\mathrm{O}$ states that are populated when the incoming $\ensuremath{\alpha}$ particles exceed the reaction $Q$ value. Thanks to the excellent energy performance of the Demonstrator's germanium detectors, these characteristic photons can be clearly observed in the calibration data. Facilitated by Geant4 simulations, a comparison between the observed 6129-keV photon rates and predictions by a talys-based software was performed. The measurements and predictions were found to be consistent, albeit with large statistical uncertainties. This agreement provides support for background projections from $(\ensuremath{\alpha},n)$ reactions in future double-beta decay search efforts.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".