Search for Sources of Astrophysical Neutrinos Using Seven Years of IceCube Cascade Events
Bibliographic record
Abstract
Low-background searches for astrophysical neutrino sources anywhere in the sky can be performed using cascade events induced by neutrinos of all flavors interacting in IceCube with energies as low as ~1 TeV. Previously we showed that, even with just two years of data, the resulting sensitivity to sources in the southern sky is competitive with IceCube and ANTARES analyses using muon tracks induced by charge current muon neutrino interactions—especially if the neutrino emission follows a soft energy spectrum or originates from an extended angular region. Here, we extend that work by adding five more years of data, significantly improving the cascade angular resolution, and including tests for point-like or diffuse Galactic emission to which this data set is particularly well suited. For many of the signal candidates considered, this analysis is the most sensitive of any experiment to date. No significant clustering was observed, and thus many of the resulting constraints are the most stringent to date. In this paper we will describe the improvements introduced in this analysis and discuss our results in the context of other recent work in neutrino astronomy.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".