The Na-O anticorrelation in horizontal branch stars
Bibliographic record
Abstract
We used FLAMES+GIRAFFE (Medusa mode) at the VLT to obtain moderately high resolution spectra for 30 red horizontal branch (RHB) stars, 4 RR Lyrae variables, and 17 blue horizontal branch (BHB) stars in the low-concentration, moderately metal-rich globular cluster NGC 6723 ([Fe/H] = −1.22 ± 0.08 from our present sample). The spectra were optimized to derive O and Na abundances. In addition, we obtained abundances for other elements, including N, Fe, Mg, Ca, Ni, and Ba. We used these data to discuss the evidence of a connection between the distribution of stars along the horizontal branch (HB) and the multiple populations that are typically present in globular clusters. We found that all RHB and most (13 out of 17) BHB stars are O-rich, Na-poor, and N-poor; these stars probably belong to the first stellar generation in this cluster. Only the four warmest observed stars are (moderately) O-poor, Na-rich, and N-rich, and they probably belong to the second generation. While our sample is not fully representative of the whole HB population in NGC 6723, our data suggest that in this cluster only HB stars warmer than ~9000 K, that is one fourth of the total, belong to the second generation, if at all. Since in many other clusters this fraction is about two thirds, we conclude that the fraction of first/second generation in globular clusters may be strongly variable. In addition, the wide range in colour of chemically homogeneous first-generation HB stars requires a considerable spread in mass loss (>0.10 M⊙). The reason for this spread is yet to be understood. Finally, we found a high Ba abundance, with a statistically significant radial abundance gradient.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".