All-flavor Multi-Channel Analysis of the Astrophysical Neutrino Spectrum with IceCube
Bibliographic record
Abstract
The spectral shape and flavor composition of the high-energy astrophysical neutrino flux can contain important information about the sources and processes which produce it. The IceCube Neutrino Observatory has previously demonstrated the ability to observe neutrinos of all flavors by selecting events which interact within the detector volume. Sensitivity to charged current muon neutrino interactions in or close to the detector has also been shown by selecting muon track events whose directions indicate passage through the Earth. We present an updated analysis of starting events using 6 years of IceCube data taken from 2010--2016 focusing on energies from the PeV region down to 1 TeV, far below the threshold of the original data sample used in the initial discovery of the astrophysical flux. Astrophysical neutrinos remain the dominant component in the southern sky down to 10 TeV. We then also perform a unified analysis of the flavor and spectrum implications of this sample when combined with the recently published data on $\nu_\mu$ induced muon tracks as well as recent work to identify candidate $\nu_\tau$ events.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".