The age distribution of stellar clusters in M83
Bibliographic record
Abstract
Abstract In order to empirically determine the time-scale and environmental dependence of stellar cluster disruption, we have undertaken an analysis of the unprecedented multipointing (seven), multiwavelength (U, B, V, Hα, and I) Hubble Space Telescope imaging survey of the nearby, face-on spiral galaxy M83. The images are used to locate stellar clusters and stellar associations throughout the galaxy. Estimation of cluster properties (age, mass, and extinction) was done through a comparison of their spectral energy distributions with simple stellar population models. We constructed the largest catalogue of stellar clusters and associations in this galaxy to-date, with ∼1800 sources with masses above ∼5000 M⊙ and ages younger than ∼300 Myr. In this Letter, we focus on the age distribution of the resulting clusters and associations. In particular, we explicitly test whether the age distributions are related with the ambient environment. Our results are in excellent agreement with previous studies of age distributions in the centre of the galaxy, which gives us confidence to expand out to search for similarities or differences in the other fields which sample different environments. We find that the age distribution of the clusters inside M83 varies strongly as a function of position within the galaxy, indicating a strong correlation with the galactic environment. If the age distributions are approximated as a power law of the form ${\frac{\mathrm{d} N}{\mathrm{d}t}}\propto t^{\zeta }$, we find ζ values between 0 and −0.62 (ζ ∼ −0.40 for the whole galaxy), in good agreement with previous results and theoretical predictions.
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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".