Modelling self-pollution of globular clusters from asymptotic giant branch stars
Bibliographic record
Abstract
A self-consistent model of the chemical evolution of the globular cluster NGC 6752 is presented to test a popular theory that observed abundance anomalies are due to ‘internal pollution’ from intermediate-mass asymptotic giant branch stars. We simulated the chemical evolution of the intracluster medium under the assumption that the products of Type II supernovae are completely expelled from the globular cluster, whereas the material ejected from stars with m≲ 7 M⊙ is retained, due to their weak stellar winds. By tracing the chemical evolution of the intracluster gas we have tested an internal pollution scenario, in which the Na- and Al-enhanced ejecta from intermediate-mass stars is either accreted on to the surfaces of other stars, or goes toward forming new stars. The observed spread in Na and Al was reproduced, but not the O–Na and Mg–Al anticorrelations. In particular, neither O nor Mg are sufficiently depleted to account for the observations. We predict that the Mg content of Na-rich cluster stars should be overwhelmingly dominated by the 25,26Mg isotopes, whereas the latest data show only a mild 26Mg enhancement and no correlation with 25Mg. Furthermore, stars bearing the imprint of intermediate-mass stellar ejecta are predicted to be strongly enhanced in both C and N, in conflict with the empirical data. We show that the NGC 6752 data are not matched by a model incorporating detailed nucleosynthetic yields from asymptotic giant branch stars. Although these stars do show the hot hydrogen burning that seems to be required to explain the observations, this is accompanied by helium burning, producing primary C, N, Mg and Na (via hot-bottom burning) which do not match the observations. Based on current theories of intermediate-mass stellar nucleosynthesis, we conclude that these stars are not responsible for most of the observed globular cluster abundance anomalies.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".