POPULATION PARAMETERS OF INTERMEDIATE-AGE STAR CLUSTERS IN THE LARGE MAGELLANIC CLOUD. II. NEW INSIGHTS FROM EXTENDED MAIN-SEQUENCE TURNOFFS IN SEVEN STAR CLUSTERS
Bibliographic record
Abstract
We discuss new photometry from high-resolution images of seven intermediate-age (1–2 Gyr) star clusters in the Large Magellanic Cloud taken with the Advanced Camera for Surveys on board the Hubble Space Telescope . We fit color–magnitude diagrams (CMDs) with several different sets of theoretical isochrones and determine systematic uncertainties for population parameters when derived using any one set of isochrones. The cluster CMDs show several interesting features, including extended main-sequence turnoff (MSTO) regions, narrow red giant branches, and clear sequences of unresolved binary stars. We show that the extended MSTOs are not caused by photometric uncertainties, contamination by field stars, or the presence of binary stars. Enhanced helium abundances in a fraction of cluster stars are also ruled out as the reason for the extended MSTOs. Quantitative comparisons with simulations indicate that the MSTO regions are better described by a spread in ages than by a bimodal age distribution, although we cannot formally rule out the latter for the three lowest-mass clusters in our sample (which have masses lower than ∼3 × 10 4 M ☉ ). This conclusion differs from that of some previous works which suggested that the age distribution in massive clusters in our sample is bimodal. This suggests that any secondary star formation occurred in an extended fashion rather than through short bursts. We discuss these results in the context of the nature of multiple stellar populations in star clusters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".