The impact of (n,γ) reaction rate uncertainties on the predicted abundances of i-process elements with 32 ≤ <i>Z</i> ≤ 48 in the metal-poor star HD94028
Bibliographic record
Abstract
ABSTRACT Several anomalous elemental abundance ratios have been observed in the metal-poor star HD94028. We assume that its high [As/Ge] ratio is a product of a weak intermediate (i) neutron-capture process. Given that observational errors are usually smaller than predicted nuclear physics uncertainties, we have first set-up a benchmark one-zone i-process nucleosynthesis simulation results of which provide the best fit to the observed abundances. We have then performed Monte Carlo simulations in which 113 relevant (n,γ) reaction rates of unstable species were randomly varied within Hauser–Feshbach model uncertainty ranges for each reaction to estimate the impact on the predicted stellar abundances. One of the interesting results of these simulations is a double-peaked distribution of the As abundance, which is caused by the variation of the 75Ga (n,γ) cross-section. This variation strongly anticorrelates with the predicted As abundance, confirming the necessity for improved theoretical or experimental bounds on this cross-section. The 66Ni (n,γ) reaction is found to behave as a major bottleneck for the i-process nucleosynthesis. Our analysis finds the Pearson product–moment correlation coefficient rP > 0.2 for all of the i-process elements with 32 ≤ Z ≤ 42, with significant changes in their predicted abundances showing up when the rate of this reaction is reduced to its theoretically constrained lower bound. Our results are applicable to any other stellar nucleosynthesis site with the similar i-process conditions, such as Sakurai’s object (V4334 Sagittarii) or rapidly accreting white dwarfs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".