UVIT<i>–HST</i>–<i>GAIA</i>view of NGC 288: a census of the hot stellar population and its properties from UV
Bibliographic record
Abstract
A complete census of the blue horizontal branch (BHB) and blue straggler star (BSS) population within a 10′ radius from the centre of the globular cluster NGC 288 is presented, based on images from the Ultraviolet Imaging Telescope (UVIT). The UV and UV−optical colour–magnitude diagrams (CMDs) are constructed by combining the UVIT, HST-ACS and ground data and are compared with the Bag of Stellar Tracks and Isochrones (BaSTI) isochrones generated for UVIT filters. We used stellar proper motion data from GAIA DR2 to select the cluster members. Our estimations of the temperature distribution of 110 BHB stars reveal two peaks, with the main peak at Teff ∼ 10 300 K, and with the distribution extending up to Teff ∼ 18 000 K. We identify the well-known photometric gaps, including the Grundahl jump (G-jump) in the BHB distribution, which are located between the peaks. We detect a plateau in the far-ultraviolet (FUV) magnitude for stars hotter than Teff ∼ 11 500 K (G-jump), which could be caused by atomic diffusion. We detect two extreme horizontal branch (EHB) candidates, with temperatures ranging from 29 000 to 32 000 K. The radial distribution of 68 BSSs suggests that the bright BSSs are more centrally concentrated than the faint BSSs and the BHB stars. We find that the BSSs have a mass range of 0.86–1.25 M⊙ and an age range of 2–10 Gyr, with peaks at 1 M⊙ and 4 Gyr respectively. This study showcases the importance of combining UVIT with HST, ground and GAIA data in deriving HB and BSS properties.
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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 | 0.001 | 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) | 0.006 | 0.002 |
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".