THE BORON-TO-CARBON ABUNDANCE RATIO AND GALACTIC PROPAGATION OF COSMIC RADIATION
Bibliographic record
Abstract
In two long-duration balloon flights in 2003 and 2006, the TRACER cosmic-ray detector has measured the energy spectra and the absolute intensities of the cosmic-ray nuclei from boron ( Z = 5) to iron ( Z = 26) up to very high energies. In particular, the second flight has led to results on the energy spectrum of the secondary boron nuclei, and on the boron abundance relative to that of the heavier primary parent nuclei, commonly quantified as the "B/C abundance ratio." The energy dependence of this ratio, now available up to about 2 TeV amu −1 , provides a measure for the energy dependence of cosmic-ray propagation through the Galaxy, and for the shape of the cosmic-ray source energy spectrum. We use a Leaky-Box approximation of cosmic-ray propagation to obtain constraints on the relevant parameters on the basis of the results of TRACER and of other measurements. This analysis suggests that the source energy spectrum is a relatively soft power law in energy E −α , with spectral exponent α = 2.37 ± 0.12, and that the propagation path length Λ( E ) is described by a power law in energy with exponent δ = 0.53 ± 0.06, but may assume a constant residual value Λ 0 at high energy. The value of Λ 0 is not well constrained but should be less than about 0.8 g cm −2 . Finally, we compare the data with numerical solutions of a diffusive reacceleration model, which also indicates a soft source spectrum.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".