The GALEX Ultraviolet Virgo Cluster Survey (GUViCS)
Bibliographic record
Abstract
We use the GALEX data of the GUViCS survey to construct the near-ultraviolet (NUV) luminosity function of the Virgo cluster over ~300 deg2, an area covering the cluster and its surrounding regions up to ~1.8 virial radii. The NUV luminosity function is also determined for galaxies of different morphological types and NUV−i colours, and for the different substructures within the cluster. These luminosity functions are robust vs. statistical corrections since based on a sample of 833 galaxies mainly identified as cluster members with spectroscopic redshift (808) or high-quality optical scaling relations (10). We fit these luminosity functions with a Schechter function, and compare the fitted parameters with those determined for other nearby clusters and for the field. The faint end slope of the Virgo NUV luminosity function (α = −1.19), here sampled down to ~NUV = −11.5 mag, is significantly flatter than the value measured in other nearby clusters and similar to the field value. Similarly, M∗ = −17.56 is one to two magnitudes fainter than measured in Coma, A1367, the Shapley supercluster, and the field. These differences seem to be due to the quite uncertain statistical corrections and the small range in absolute magnitude sampled in these clusters. We do not observe strong systematic differences in the overall NUV luminosity function of the core of the cluster with respect to that of its periphery. We note, however, that the relative contribution of red and blue galaxies at the faint end is inverted, with red quiescent objects dominating the core of the cluster and star forming galaxies dominating beyond one virial radius. This observational evidence is discussed in the framework of galaxy evolution in dense environments.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".