RE-EVALUATION OF THE<sup>16</sup>O(<i>N</i>,<i>γ</i>)<sup>17</sup>O CROSS SECTION AT ASTROPHYSICAL ENERGIES AND ITS ROLE AS A NEUTRON POISON IN THE<i>s</i>-PROCESS
Bibliographic record
Abstract
The doubly magic nucleus 16 O has a small neutron-capture cross section of just a few tens of microbarns in the astrophysical energy region. Despite this, 16 O plays an important role as a neutron poison in the astrophysical slow neutron capture ( s ) process due to its high abundance. We present in this paper a re-evaluation of the available experimental data for 16 O( ) 17 O and derive a new recommendation for the Maxwellian-averaged cross sections between kT = 5 and 100 keV. Our new recommendations are lower up to kT = 60 keV compared to the previously recommended values but up to 14% higher at kT = 100 keV. We explore the impact of this different energy dependence on the weak s -process during core helium burning ( kT = 26 keV) and shell carbon burning ( kT = 90 keV) in massive stars where 16 O is the most abundant isotope.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".