FORMATION AND EVOLUTION OF BLUE STRAGGLERS IN 47 TUCANAE
Bibliographic record
Abstract
ABSTRACT Blue stragglers (BSS) are stars whose position in the color–magnitude diagram (CMD) places them above the main sequence (MS) turn-off (TO) point of a star cluster. Using data from the core of 47 Tuc in the ultraviolet (UV), we have identified various stellar populations in the CMD, and used their radial distributions to study the evolution and origin of BSS, and obtain a dynamical estimate of the mass of BSS systems. When we separate the BSS into two samples by their magnitude, we find that the bright BSS show a much more centrally concentrated radial distribution and thus higher mass estimate (over twice the TO mass for these BSS systems), suggesting an origin involving triple or multiple stellar systems. In contrast, the faint BSS are less concentrated, with a radial distribution similar to the MS binaries, pointing to the MS binaries as the likely progenitors of these BSS. Putting our data together with available photometric data in the visible and using MESA evolutionary models, we calculate the expected number of stars in each evolutionary stage for the normal evolution of stars and the number of stars coming from the evolution of BSS. The results indicate that BSS have a post-MS evolution comparable to that of a normal star of the same mass and a MS BSS lifetime of about 200–300 Myr. We also find that the excess population of asymptotic giant branch stars in 47 Tuc is due to evolved BSS.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 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".