The GALEX Ultraviolet Virgo Cluster Survey (GUViCS)
Bibliographic record
Abstract
Context. Several galaxies in the Virgo cluster are known to have large H i gas tails related to a recent ram-pressure stripping event. The Virgo cluster has been extensively observed at 1539 Å in the far-ultraviolet for the GALEX Ultraviolet Virgo Cluster Survey (GUViCS), and in the optical for the Next Generation Virgo Survey (NGVS), allowing a study of the stellar emission potentially associated with the gas tails of 8 cluster members. On the theoretical side, models of ram-pressure stripping events have started to include the physics of star formation. Aims. We aim to provide quantitative constraints on the amount of star formation taking place in the ram-pressure stripped gas, mainly on the basis of the far-UV emission found in the GUViCS images in relation with the gas content of the tails. Methods. We have performed three comparisons of the young stars emission with the gas column density: visual, pixel-by-pixel, and global. We have compared our results to other observational and theoretical studies. Results. We find that the level of star formation taking place in the gas stripped from galaxies by ram-pressure is low with respect to the available amount of gas. Star formation is lower by at least a factor 10 compared to the predictions of the Schmidt Law as determined in regular spiral galaxy disks. It is also lower than measured in dwarfs galaxies and the outer regions of spirals, and than predicted by some numerical simulations. We provide constraints on the star formation efficiency in the ram-pressure stripped gas tails, and compare these with current models.
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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 | 0.001 | 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) | 0.003 | 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".