New Public Neutrino Alerts for Clusters of IceCube Events
Bibliographic record
Abstract
The IceCube Neutrino Observatory searches for the origins of astrophysical neutrinos using various techniques to overcome the significant backgrounds produced by cosmic-ray air showers. One such technique involves combining the neutrino data with other cosmic messengers to identify spatial and temporal correlations. IceCube contributes to multi-messenger astrophysics (MMA) by providing alerts for interesting events observed in the detector. The Gamma-ray Follow-Up (GFU) cluster alert system is one stream that identifies potential neutrino flares in realtime, producing around 20 alerts per year. GFU-cluster alerts have been privately shared with Imaging Air Cherenkov Telescopes (IACTs) through memoranda of understanding since IceCube’s predecessor, AMANDA. To preserve blindness to the full behavior of our data, the current system mutes updates from sources following the initial GFU-cluster alert sent, preventing further updates until the activity drops below the alert threshold. With growing knowledge of the potential environments that produce astrophysical neutrinos and to foster open collaboration, the GFU-cluster alerts will shift to be publicly shared. Additionally, the new alert platform will provide all above-threshold information such that the source behavior after the initial alert is not obscured. The above threshold data will be distributed through an interactive website that will update the community on the status of active GFU-cluster alerts. This presentation will introduce the new GFU-cluster platform and the accompanying website, soon to be accessible to the MMA community.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.022 |
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".