THE SNAPSHOT<i>HUBBLE</i><i>U</i>-BAND CLUSTER SURVEY (SHUCS). II. THE STAR CLUSTER POPULATION OF NGC 2997
Bibliographic record
Abstract
We study the star cluster population of NGC 2997, a giant spiral galaxy located at 9.5 Mpc and targeted by the Snapshot Hubble U -band Cluster Survey (SHUCS). Combining our U -band imaging from SHUCS with archival BVI imaging from the Hubble Space Telescope , we select a high confidence sample of clusters in the circumnuclear ring and disk through a combination of automatic detection procedures and visual inspection. The cluster luminosity functions in all four filters can be approximated by power laws with indices of −1.7 to −2.3. Some deviations from pure power-law shape are observed, hinting at the presence of a high-mass truncation in the cluster mass function. However, upon inspection of the cluster mass function, we find it is consistent with a pure power law of index −2.2 ± 0.2 despite a slight bend at ∼2.5 × 10 4 M ☉ . No statistically significant truncation is observed. From the cluster age distributions, we find a low rate of disruption (ζ ∼ −0.1) in both the disk and circumnuclear ring. Finally, we estimate the cluster formation efficiency (Γ) over the last 100 Myr in each region, finding 7% ± 2% for the disk, 12% ± 4% for the circumnuclear ring, and 10% ± 3% for the entire UBVI footprint. This study highlights the need for wide-field UBVI coverage of galaxies to study cluster populations in detail, though a small sample of clusters can provide significant insight into the characteristics of the population.
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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 | 0.002 | 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) | 0.003 | 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".