Silicon and Carbon Isotopic Ratios in AGB Stars: SiC Grain Data, Models, and the Galactic Evolution of the Si Isotopes
Bibliographic record
Abstract
Presolar SiC grains of the mainstream, Y, and Z type are believed to come from carbon stars. We compared their C and Si isotopic ratios with theoretical models for the envelope compositions of AGB stars. Two sets of models (FRANEC and Monash) use a range of stellar masses (1.5-5 M ☉ ) and metallicities, different prescriptions for mass loss, and two sets of neutron-capture cross sections for the Si isotopes. They predict that the shifts in Si isotopic ratios and the increase of 12 C/ 13 C in the envelope during third dredge-up are higher for higher stellar mass, lower metallicity, and lower mass-loss rate. Because the 22 Ne neutron source dominates Si nucleosynthesis, the effect of the 13 C source is negligible. Comparison of the model predictions with grain data confirms an AGB origin for these grains, with Y and Z grains having originated in stars with lower than solar metallicity. The Si isotopic ratios of the Z grains favor the Si cross sections by Guber et al. over those by Bao et al. The 12 C/ 13 C ratios of low-metallicity models are much higher than those found in Z grains, and cool bottom processing must be invoked to explain the grains' C isotopic ratios. By combining Z grain Si data with the models, we determined the evolution of the 29 Si/ 28 Si ratio in the Galaxy as function of metallicity Z . At Z < 0.01 this ratio rises much faster than current Galactic evolution models predict and suggests an early source of the heavy Si isotopes not considered in these models.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".