Search for ultrahigh-energy tau neutrinos with IceCube
Bibliographic record
Abstract
The first dedicated search for ultrahigh-energy (UHE) tau neutrinos of astrophysical origin was performed using the IceCube detector in its 22-string configuration with an instrumented volume of roughly $0.25\text{ }\text{ }{\mathrm{km}}^{3}$. The search also had sensitivity to UHE electron and muon neutrinos. After application of all selection criteria to approximately 200 live-days of data, we expect a background of $0.60\ifmmode\pm\else\textpm\fi{}0.19(\mathrm{stat})\genfrac{}{}{0}{}{+0.56}{\ensuremath{-}0.58}(\mathrm{syst})$ events and observe three events, which after inspection, emerge as being compatible with background but are kept in the final sample. Therefore, we set an upper limit on neutrinos of all flavors from UHE astrophysical sources at 90% C.L. of ${E}_{\ensuremath{\nu}}^{2}{\ensuremath{\Phi}}_{90}({\ensuremath{\nu}}_{\mathrm{x}})<16.3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}8}\text{ }\text{ }\mathrm{GeV}\text{ }{\mathrm{cm}}^{\ensuremath{-}2}\text{ }{\mathrm{sr}\text{ }}^{\ensuremath{-}1}\text{ }{\mathrm{s}}^{\ensuremath{-}1}$ over an estimated primary neutrino energy range of 340 TeV to 200 PeV.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.004 | 0.001 |
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".