An updated list of target sources for IceCube neutrino cluster alerts
Bibliographic record
Abstract
Multimessenger astronomy seeks to uncover the origins of cosmic rays and neutrinos. The IceCube Neutrino Observatory plays a key role in monitoring the sky for revealing high energy neutrinos and neutrino time clusters possibly associated with astrophysical sources, issuing alerts to the astrophysical community for significant excesses. This enables joint observations with other astronomical facilities that could reveal the hidden mechanisms behind the most extreme environments in the Universe. In particular, since 2006 the Gamma-ray Follow-Up (GFU) program shares cluster alerts with partner Imaging Air Cherenkov Telescopes. The faint cosmic signals, searched against large atmospheric backgrounds, are widely masked by the statistical penalties that arise when scanning the full sky in an unbiased way. Hence, targeted analyses of pre-selected neutrino source candidates have proven to increase our search sensitivity. Our understanding of astrophysical environments has improved in recent years, with evidence of neutrino emission from the blazar TXS 0506+056 and the Seyfert galaxy NGC 1068. The aim of expanding observational possibilities and engaging the broader scientific community through public cluster alerts has motivated the creation of a new list of target sources to be monitored by IceCube. This contribution presents the systematic compilation of this list, which extends the well-established focus on gamma-ray bright active galactic nuclei (AGN) to include X-ray bright AGN and binary systems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.016 |
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".