Bibliographic record
Abstract
ABSTRACT The initial sizes and masses of massive star clusters provide information about the cluster formation process and also determine how cluster populations are modified and destroyed, which have implications for using clusters as tracers of galaxy assembly. Young massive cluster populations are often assumed to be unchanged since cluster formation; therefore, their distributions of masses and radii are used as the initial values. However, the first few hundred million years of cluster evolution does change both cluster mass and cluster radius, through both internal and external processes. In this paper, we use a large suite of N-body cluster simulations in an appropriate tidal field to determine the best initial mass and initial size distributions of young clusters in the nearby galaxy M83. We find that the initial masses follow a power-law distribution with a slope of −2.7 ± 0.4 , and the half-mass radii follow a lognormal distribution with a mean of 2.57 ± 0.04 pc and a dispersion of 1.59 ± 0.01 pc. The corresponding initial projected half-light radius function has a mean of 2.7 ± 0.3 pc and a dispersion of 1.7 ± 0.2 pc. The evolution of the initial mass and size distribution functions is consistent with mass-loss and expansion due to stellar evolution, independent of the external tidal field and the cluster’s initial density profile. Observed cluster sizes and masses should not be used as the initial values, even when clusters are only a few hundred million years old.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".