Galactic and extragalactic core-collapse supernova neutrino flux detection in the LEGEND muon veto
Bibliographic record
Abstract
Parallel talk presented at the XXI International Workshop on Neutrino Telescopes - Padova 29 September - 3 October 2025 (https://agenda.infn.it/event/44606/) On behalf of the LEGEND Collaboration Abstract: The LEGEND Collaboration advances an experimental program to search for the neutrinoless double-beta decay of 76 Ge.It has recently released the first results on the decay search based on 61 kg yr of data collected by the first stage of the experiment, LEGEND-200. It operates high-purity germanium (HPGe) detectors enriched in 76 Ge immersed in a cryostat filled with pure liquid argon. The cryostat is deployed in a tank filled with 590 m3 of purifiedwater, instrumented with photomultiplier tubes to tag cosmic-ray induced muon events, and to passively shield the detectors against environmental radioactivity.The second stage of the experiment, LEGEND-1000, aims to operate up to one ton of HPGe detectors enriched in 76 Ge with different proposals to optimize the water tank features.In this presentation, we explore the detection capabilities and sensitivity of the LEGEND muon veto in both phases of the experiment to the neutrino flux from core-collapse supernovae. The ability to identify the time of black hole formation is also discussed. This work is supported by the U.S. DOE, and the NSF, the LANL, ORNL and LBNL LDRD programs; the European ERC and Horizon programs; the German DFG, BMBF, and MPG; the Italian INFN; the Polish NCN and MNiSW; the Czech MEYS; the Slovak RDA; the Swiss SNF; the UK STFC; the Canadian NSERC and CFI; the LNGS and SURF facilities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".