VERTICO
Bibliographic record
Abstract
We analyse cold-gas distributions in Virgo cluster galaxies using resolved observations of CO(2-1), which traces molecular hydrogen (H2), and H I from the Virgo Environment Traced In CO (VERTICO) and VLA Imaging of Virgo in Atomic Gas (VIVA) surveys. From a theoretical perspective, it is expected that environmental processes in clusters will have a stronger influence on diffuse atomic gas compared to the relatively dense molecular gas component, and that these environmental perturbations can compress the cold interstellar medium in cluster galaxies, leading to elevated star formation. In this work we observationally test these predictions for star-forming satellite galaxies within the Virgo cluster. We divided our Virgo galaxy sample into H I-normal, H I-tailed, and H I-truncated classes and show, unsurprisingly, that the H I-tailed galaxies have the largest quantitative H I asymmetries. We also compared Virgo galaxies to a control sample of non-cluster galaxies and find that the former, on average, have H I asymmetries that are 40 ± 10% larger than the latter. There is less separation between control, H I-normal, H I-tailed, and H I-truncated galaxies in terms of H2 asymmetries, and on average, Virgo galaxies have H2 asymmetries that are only marginally (20 ± 10%) larger than the control sample. We find a weak correlation between H I and H2 asymmetries over our entire sample, but a stronger correlation for the galaxies that are strongly impacted by environmental perturbations. Finally, we divided the discs of the H I-tailed Virgo galaxies into a leading half and trailing half according to the observed tail direction. We find evidence for excess molecular gas mass on the leading halves of the disc. This excess molecular gas is accompanied by an excess in the star formation rate such that the depletion time is, on average, unchanged.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.259 | 0.164 |
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".