Light sterile neutrino sensitivity at the nuSTORM facility
Bibliographic record
Abstract
A facility that can deliver beams of electron and muon neutrinos from the decay of a stored muon beam has the potential to unambiguously resolve the issue of the evidence for light sterile neutrinos that arises in short-baseline neutrino oscillation experiments and from estimates of the effective number of neutrino flavors from fits to cosmological data. In this paper, we show that the nuSTORM facility, with stored muons of $3.8\text{ }\mathrm{GeV}/\mathrm{c}\text{ }\ifmmode\pm\else\textpm\fi{}\text{ }10%$, will be able to carry out a conclusive muon neutrino appearance search for sterile neutrinos and test the LSND and MiniBooNE experimental signals with $10\ensuremath{\sigma}$ sensitivity, even assuming conservative estimates for the systematic uncertainties. This experiment would add greatly to our knowledge of the contribution of light sterile neutrinos to the number of effective neutrino flavors from the abundance of primordial helium production and from constraints on neutrino energy density from the cosmic microwave background. The appearance search is complemented by a simultaneous muon neutrino disappearance analysis that will facilitate tests of various sterile neutrino models.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".