Search for neutron dark decay: <i>n</i> → χ + <i>e</i><sup>+</sup><i>e</i><sup>−</sup>
Bibliographic record
Abstract
In January, 2018, Fornal and Grinstein proposed that a previously unobserved neutron decay branch to a dark matter particle (χ) could account for the discrepancy in the neutron lifetime observed in two different types of experiments. One of the possible final states discussed includes a single χ along with an e+e− pair. We use data from the UCNA (Ultracold Neutron Asymmetry) experiment to set limits on this decay channel. Coincident electron-like events are detected with ∼ 4π acceptance using a pair of detectors that observe a volume of stored Ultracold Neutrons (UCNs). We use the timing information of coincidence events to select candidate dark sector particle decays by applying a timing calibration and selecting events within a physically-forbidden timing region for conventional n → p + e- + ν̅e decays. The summed kinetic energy (Ee+e−) from such events is reconstructed and used to set limits, as a function of the χ mass, on the branching fraction for this decay channel.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".