Energy-dependent flavor ratios of High-energy Astrophysical Neutrinos
Bibliographic record
Abstract
Measuring the flavor composition of the TeV-PeV astrophysical neutrinos, i.e., the ratio of the flux of neutrinos of each flavor to the total flux sheds light on their production mechanisms and on the action of flavor transitions during propagation. So far, measurements of the flavor composition, based on IceCube data, have of necessity assumed that it is independent of neutrino energy, on account of the limited size of the data sample. However, the natural expectation is for the flavor composition to vary with neutrino energy, due to the presence of different neutrino production mechanisms at different energies, or to flavor-changing new physics. Therefore, we look for signs of the energy dependence of the flavor composition in recent IceCube public data and show forecasts for next-generation neutrino telescopes: Baikal-GVD, IceCube-Gen2, KM3NeT, P-ONE, TAMBO, and TRIDENT. We find that combing the data samples of telescopes in the future is critical to pin down changes in the flavor composition with energy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".