A Virgo Environmental Survey Tracing Ionised Gas Emission (VESTIGE)
Bibliographic record
Abstract
The Virgo Environmental Survey Tracing Ionised Gas Emission (VESTIGE) is a blind narrow-band H α + [NII] imaging survey of the Virgo cluster carried out with MegaCam at the Canada-French-Hawaii telescope. We use a new set of data extracted from VESTIGE to study the impact of the hostile cluster environment on the star formation process down to the scale of HII regions (∼50 pc). Here, HII regions are identified and their parameters measured using the HII PHOT code on a sample of 114 late-type galaxies spanning a wide range in morphological type (Sa-Sd, Im, BCD), stellar mass (10 6.5 ≤ M star ≤ 10 11 M ⊙ ), and star formation activity (10 −3 ≤ SFR ≤ 10 M ⊙ yr −1 ). Owing to the exquisite average resolution of the VESTIGE data (0.65 arcsec), we detect 11302 HII regions with an H α luminosity L (H α ) ≥ 10 37 erg s −1 . We show that the typical number of HII regions in gas-stripped objects is significantly lower than in healthy late-types of similar stellar mass. We also show that in these gas-stripped galaxies the number of HII regions significantly drops outside the effective radius, suggesting that the quenching process occurs outside-in, in agreement with other multifrequency observations. These new results consistently confirm that the main mechanism responsible for the decrease of the star formation activity observed in cluster galaxies is ram pressure, allowing us to discard other milder processes such as starvation or strangulation, which are unable to reproduce the observed radially truncated profiles.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".