The Luminosity Function of Star Clusters in Spiral Galaxies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Star clusters in 6 nearby spiral galaxies are examined using archive images from HST/WFPC2. The galaxies have previously been studied from the ground and some of them are known to possess rich populations of "young massive clusters" (YMCs). Comparison with the HST images indicates a success-rate of about 75% for the ground-based cluster detections, with typical contaminants being blends or loose groupings of several stars in crowded regions. The luminosity functions (LFs) of cluster candidates identified on the HST images are analyzed and compared with existing data for the Milky Way and the LMC. The LFs are well approximated by power-laws of the form dN(L)/dL ~ L^alpha, with slopes in the range -2.4<alpha<-2.0. The steeper slopes tend to be found among fits covering brighter magnitude intervals, although direct hints of a variation in the LF slope with magnitude are seen only at low significance in two galaxies. The surface density of star clusters at a reference magnitude of M(V)=-8 scales with the mean star formation rate per unit area, Sigma(SFR). Assuming that the LF can be generally expressed as a power-law with normalization proportional to the galaxy area (A) and Sigma(SFR), the maximum cluster luminosity expected in a galaxy from random sampling of the LF is estimated as a function of Sigma(SFR) and A. The predictions agree well with existing observations of galaxies spanning a wide range of Sigma(SFR) values, suggesting that sampling statistics play an important role in determining the maximum observed luminosities of young star clusters in galaxies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it