Search for a time-varying electron antineutrino signal at Daya Bay
Bibliographic record
Abstract
A search for a time-varying ${\overline{\ensuremath{\nu}}}_{e}$ signal was performed with 621 days of data acquired by the Daya Bay Reactor Neutrino Experiment over 704 calendar days. The time spectrum of the measured ${\overline{\ensuremath{\nu}}}_{e}$ flux normalized to its prediction was analyzed with a Lomb-Scargle periodogram, which yielded no significant signal for periods ranging from 2 hours to nearly 2 years. The normalized time spectrum was also fit for a sidereal modulation under the Standard Model Extension (SME) framework to search for Lorentz and $CPT$ violation (LV-CPTV). Limits were obtained for all six flavor pairs $\overline{e}\overline{\ensuremath{\mu}},\overline{e}\overline{\ensuremath{\tau}}$, $\overline{\ensuremath{\mu}}\overline{\ensuremath{\tau}}$, $\overline{e}\overline{e},\overline{\ensuremath{\mu}}\overline{\ensuremath{\mu}}$ and $\overline{\ensuremath{\tau}}\overline{\ensuremath{\tau}}$ by fitting them one at a time, constituting the first experimental constraints on the latter three. Daya Bay's high statistics and unique layout of multiple directions from three pairs of reactors to three experimental halls allowed the simultaneous constraint of individual SME LV-CPTV coefficients without assuming others contribute negligibly, a first for a neutrino experiment.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".