STEP survey – II. Structural analysis of 170 star clusters in the SMC
Bibliographic record
Abstract
ABSTRACT We derived surface brightness profiles in the g band for 170 Small Magellanic Cloud (SMC) star clusters (SCs) mainly located in the central region of the galaxy. We provide a set of homogeneous structural parameters obtained by fitting Elson–Fall–Freeman and King models. Through a careful analysis of their colour–magnitude diagrams we also supply the ages for a subsample of 134 SCs. For the first time, such a large sample of SCs in the SMC is homogeneously characterized in terms of their sizes, luminosities, and masses, widening the probed region of the parameter space, down to hundreds of solar masses. We used these data to explore the evolution of the SC’s structural parameters with time. In particular, we confirm the existence of a physical mechanism that induces an increase of the core radius after 0.3–1.0 Gyr. We suggest that cluster mass could be the main parameter driving the inner expansion, as none of the SCs having log (M/M⊙) ≤ 3.5 dex analysed in this work undergoes to such an expansion. We also detected a mass–size relationship almost over the entire range of SCs masses investigated here. Finally, our data suggest that globally the SMC SC system is dynamically evolved.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".