Search for MeV electron recoils from dark matter in EXO-200
Bibliographic record
Abstract
We present a search for electron-recoil signatures from the charged-current absorption of fermionic dark matter using the EXO-200 detector. We report an average electron-recoil background rate of $6.8\ifmmode\times\else\texttimes\fi{}{10}^{4}\text{ }\text{ }\mathrm{cts}\text{ }{\mathrm{kg}}^{\ensuremath{-}1}\text{ }{\mathrm{yr}}^{\ensuremath{-}1}\text{ }{\mathrm{keV}}^{\ensuremath{-}1}$ above 4 MeV and find no statistically significant excess over our background projection. Using a total $^{136}\mathrm{Xe}$ exposure of 234.1 kg yr, we exclude new parameter space for the charged-current absorption cross section for dark matter masses between ${m}_{\ensuremath{\chi}}=2.6--11.6\text{ }\text{ }\mathrm{MeV}$ with a minimum of $6\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}51}\text{ }{\mathrm{cm}}^{2}$ at 8.3 MeV at the 90% confidence level.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".