First all-flavor search for transient neutrino emission using 3-years of IceCube DeepCore data
Bibliographic record
Abstract
Abstract Since the discovery of a flux of high-energy astrophysical neutrinos, searches for their origins have focused primarily at TeV-PeV energies. Compared to sub-TeV searches, high-energy searches benefit from an increase in the neutrino cross section, improved angular resolution on the neutrino direction, and a reduced background from atmospheric neutrinos and muons. However, the focus on high energy does not preclude the existence of sub-TeV neutrino emission where IceCube retains sensitivity. Here we present the first all-flavor search from IceCube for transient emission of low-energy neutrinos, focusing on the energy region of 5.6-100 GeV using three years of data obtained with the IceCube-DeepCore detector. We find no evidence of transient neutrino emission in the data, thus leading to a constraint on the volumetric rate of astrophysical transient sources in the range of ∼ 705-2301 Gpc-3 yr-1 for sources following a subphotospheric energy spectrum with a mean energy of 100 GeV and a bolometric energy of 1052 erg.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".