Helium enhancements in globular cluster stars from AGB star pollution .
Bibliographic record
Abstract
Using a chemical evolution model we investigate the intriguing suggestion that there are populations of stars in some globular clusters (e.g. NGC 2808, ω Centauri) with enhanced levels of helium (Y ∼ 0.28 to 0.40) compared to the majority of the population that presumably have a primordial helium abundance. We assume that a previous generation of massive low-metallicity Asymptotic Giant Branch (AGB) stars has polluted the cluster gas via a slow stellar wind. We use two independent sets of AGB yields computed from detailed models to follow the evolution of helium, carbon, nitrogen and oxygen in the cluster gas using a Salpeter initial mass function (IMF) and a number of top-heavy IMFs. In no case were we able to fit the observational constraints, Y > 0.30 and C+N+O ≈ constant. Depending on the shape of the IMF and the yields, we either obtained Y & 0.30 and large increases in C+N+O or Y < 0.30 and C+N+O ≈ constant. These results suggest that either AGB stars alone are not responsible for the large helium enrichment or that any dredge-up from this generation of stars was less than predicted by standard 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".