Search for sterile neutrino mixing using three years of IceCube DeepCore data
Bibliographic record
Abstract
We present a search for a light sterile neutrino using three years of atmospheric neutrino data from the DeepCore detector in the energy range of approximately 10--60 GeV. DeepCore is the low-energy subarray of the IceCube Neutrino Observatory. The standard three-neutrino paradigm can be probed by adding an additional light ($\mathrm{\ensuremath{\Delta}}{m}_{41}^{2}\ensuremath{\sim}1\text{ }\text{ }{\mathrm{eV}}^{2}$) sterile neutrino. Sterile neutrinos do not interact through the standard weak interaction and, therefore, cannot be directly detected. However, their mixing with the three active neutrino states leaves an imprint on the standard atmospheric neutrino oscillations for energies below 100 GeV. A search for such mixing via muon neutrino disappearance is presented here. The data are found to be consistent with the standard three-neutrino hypothesis. Therefore, we derive limits on the mixing matrix elements at the level of $|{U}_{\ensuremath{\mu}4}{|}^{2}<0.11$ and $|{U}_{\ensuremath{\tau}4}{|}^{2}<0.15$ (90% C.L.) for the sterile neutrino mass splitting $\mathrm{\ensuremath{\Delta}}{m}_{41}^{2}=1.0\text{ }\text{ }{\mathrm{eV}}^{2}$.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".