Bibliographic record
Abstract
The elemental energy spectra of cosmic rays play an important role in understanding their acceleration and propagation. Most current results are obtained either from direct measurements by balloon or satellite detectors, or from indirect measurements by air shower detector arrays on the Earth’s surface. Imaging Air Cherenkov Telescopes (IACTs), used primarily for gamma-ray astronomy, can also be used for cosmic-ray physics. They are able to measure Cherenkov light emitted both by heavy nuclei and by secondary particles produced in their air showers, and are thus sensitive to the charge and energy of cosmic ray particles with energies of tens to hundreds of TeV. A measurement of the energy spectrum of iron nuclei, based on 71 hours of data taken by the VERITAS array of IACTs between 2009 and 2012, will be presented. The energy and other properties of the primary particle are reconstructed using a template-based likelihood fit. The event selection makes use of direct Cherenkov light, which is emitted by the primary particle before starting the air shower. A multivariate method is used to estimate the remaining background. Using these methods, the iron spectrum was measured in the energy range from 20 TeV to 500 TeV.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".