Ultra-high energy cosmic rays, cascade gamma rays, and high-energy neutrinos from gamma-ray bursts
Bibliographic record
Abstract
Gamma-ray bursts (GRBs) are sources of energetic, highly variable fluxes of γ rays, which demonstrates that they are powerful particle accelerators. Besides relativistic electrons, GRBs should also accelerate high-energy hadrons, some of which could escape cooling to produce ultra-high energy cosmic rays (UHECRs). Acceleration of high-energy hadrons in GRB blast waves will be established if high-energy neutrinos produced through photopion interactions in the blast wave are detected from GRBs. Limitations on the energy in non-thermal hadrons and the number of expected neutrinos are imposed by the fluxes from pair-photon cascades initiated in the same processes that produce neutrinos. Only the most powerful bursts at fluence levels ≳ 3 × 10 −4 erg cm −2 offer a realistic prospect for detection of ≫TeV neutrinos. Detection of high-energy neutrinos is likely if GRB blast waves have large baryon loads and Doppler factors ≲ 200. Cascade γ rays will accompany neutrino production and might already have been detected as anomalous emission components in the spectra of some GRBs. Prospects for detection of GRBs in the Milky Way are also considered.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".