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Bibliographic record
Abstract
We present $S$ factor data obtained from the Coulomb dissociation of $83\phantom{\rule{0.3em}{0ex}}\text{MeV}∕\text{nucleon}$ $^{8}\mathrm{B}$, and analyze $^{7}\mathrm{Be}$ longitudinal momentum distributions measured at 44 and $81\phantom{\rule{0.3em}{0ex}}\text{MeV}∕\text{nucleon}$ using a potential model, first-order perturbation theory, and dynamical solution of the time-dependent Schr\"odinger equation. Comparing our results with independent continuum-discretized coupled channels calculations, we study the reaction model and beam energy dependence of the $E2$ contribution to the dissociation cross section. By fitting radiative capture and Coulomb breakup data taken below relative energies of $400\phantom{\rule{0.3em}{0ex}}\text{keV}$ with potential models constrained by $^{7}\mathrm{Li}+n$ and $^{7}\mathrm{Be}+p$ elastic scattering data, we examine the mutual consistency of recent ${\mathit{S}}_{17}$ measurements and obtain a recommended value for ${S}_{17}(0)$ of $18.6\ifmmode\pm\else\textpm\fi{}0.4$ (experimental) $\ifmmode\pm\else\textpm\fi{}1.1$ (extrapolation) eV b $(1\ensuremath{\sigma})$. This result is in good agreement with recent experimental determinations of the asymptotic normalization coefficient of the valence proton wave function in $^{8}\mathrm{B}$.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.439 | 0.342 |
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".