Blue Straggler Stars: A Direct Comparison of Star Counts and Population Ratios in Six Galactic Globular Clusters
Bibliographic record
Abstract
The central regions of six Galactic globular clusters (GGCs) (M3, M80, M10, M13, M92, and NGC 288) have been imaged using HST -WFPC2 and the ultraviolet filters (F255W and F336W). The selected sample covers a large range in both central density (log ρ 0 ) and metallicity ([Fe/H]). In this paper, we present a direct cluster-to-cluster comparison of the blue straggler star (BSS) population as selected from ( m 255 , m 255 - m 336 ) color magnitude diagrams. We have found (1) that BSSs in three of the clusters (M3, M80, M92) are much more concentrated toward the center of the cluster than the red giants; because of the smaller BSS samples for the other clusters, we can only note that the BSS radial distributions are consistent with central concentration; and (2) that the specific frequency of BSSs varies greatly from cluster to cluster. The most interesting result is that the two clusters with largest BSS specific frequency are at the central density extremes of our sample: NGC 288 (lowest central density) and M80 (highest). This evidence, together with the comparison with theoretical collisional models, suggests that both stellar interactions in high-density cluster cores and at least one other alternate channel operating in low-density GGCs play an important role in the production of BSSs. We also note a possible connection between horizontal-branch morphology and blue straggler luminosity functions in these six clusters.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".