Peeking beneath the precision floor – I. Metallicity spreads and multiple elemental dispersions in the globular clusters NGC 288 and NGC 362
Bibliographic record
Abstract
ABSTRACT The view of globular clusters (GCs) as simple systems continues to unravel, revealing complex objects hosting multiple chemical peculiarities. Using differential abundance analysis, we probe the chemistry of the Type I GC, NGC 288 and the Type II GC, NGC 362 at the 2 per cent level for the first time. We measure 20 elements and find differential measurement uncertainties of the order of 0.01–0.02 dex in both clusters. The smallest uncertainties are measured for Fe i in both clusters, with an average uncertainty of ∼0.013 dex. Dispersion in the abundances of Na, Al, Ti i, Ni, Fe i, Y, Zr, Ba, and Nd are recovered in NGC 288, none of which can be explained by a spread in He. This is the first time, to our knowledge, a statistically significant spread in s-process elements and a potential spread in metallicity has been detected in NGC 288. In NGC 362, we find significant dispersion in the same elements as NGC 288, with the addition of Co, Cu, Zn, Sr, La, Ce, and Eu. Two distinct groups are recovered in NGC 362, separated by 0.3 dex in average differential s-process abundances. Given strong correlations between Al and several s-process elements, and a significant correlation between Mg and Si, we propose that the s-process rich group is younger. This agrees with asymptotic giant branch star (AGB) enrichment between generations, if there is overlap between low- and intermediate-mass AGBs. In our scenario, the older population is dominated by the r-process with a ΔLa–ΔEu ratio of −0.16 ± 0.06. We propose that the r-process dominance and dispersion found in NGC 362 are primordial.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".