A direct measurement of the 17O(α,γ)21Ne reaction in inverse kinematics and its impact on heavy element production
Bibliographic record
Abstract
During the slow neutron capture process in massive stars, reactions on light elements can both produce and absorb neutrons thereby influencing the final heavy element abundances. At low metallicities, the high neutron capture rate of 16O can inhibit s-process nucleosynthesis unless the neutrons are recycled via the 17O(α,n)20Ne reaction. The efficiency of this neutron recycling is determined by competition between the 17O(α,n)20Ne and 17O(α,γ)21Ne reactions. While some experimental data are available on the former reaction, no data exist for the radiative capture channel at the relevant astrophysical energies. The 17O(α,γ)21Ne reaction has been studied directly using the DRAGON recoil separator at the TRIUMF Laboratory. The reaction cross section has been determined at energies between 0.6 and 1.6 MeV Ecm, reaching into the Gamow window for core helium burning for the first time. Resonance strengths for resonances at 0.63, 0.721, 0.81 and 1.122 MeV Ecm have been extracted. The experimentally based reaction rate calculated represents a lower limit, but suggests that significant s-process nucleosynthesis occurs in low metallicity massive stars.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".