Bibliographic record
Abstract
Recent measurements of astrophysical neutrinos have expanded our understanding of their nature and origin. However, very little is still known about the astrophysical $\nu/\bar{\nu}$ ratio. The only prior measurement is the recent, single Glashow event seen by IceCube. Understanding the astrophysical $\nu/\bar{\nu}$ ratio has a bearing on multiple questions, including the astrophysical spectral shape and neutrino production mechanisms. This analysis uses a new approach to measuring the astrophysical muon $\nu/\bar{\nu}$ ratio at various energies. It uses inelasticity, the fraction of the initial neutrino energy carried away by the hadronic shower. Inelasticity probes the $\nu/\bar{\nu}$ ratio due to the fact that at energies below roughly 100 TeV, valence quarks dominate in deep inelastic scattering interactions, leading to different neutrino and antineutrino inelasticities and cross-sections. We use 10.3 years of IceCube data consisting of starting tracks at energies between 1 TeV and 1 PeV with a self-veto selection that enhances astrophysical event purity in the down-going direction. Based on this sample and analysis method, we present the first measurement of the astrophysical $\nu/\bar{\nu}$ ratio at sub-PeV energies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".