The Dependence Of Galaxy Properties On Group X-Ray Luminosity And Dynamics
Bibliographic record
Abstract
Star formation rates and morphologies of galaxies, particularly low-mass galaxies, are strongly linked to the properties of their environment. Using a large sample of galaxies in SDSS groups, we investigate the dependence of star formation and morphology on host properties such as the X-ray luminosity and dynamical state, while controlling for stellar and halo mass. We find that galaxy populations in groups with strong X-ray emission have preferentially low star-forming and disc fractions, both within and beyond the radius associated with the X-ray emission. Additionally, we consider the effect of group dynamics on the properties of member galaxies and the infalling galaxy population separately. We show that the fraction of both star-forming and disc galaxies are independent of dynamical state for galaxies at large group-centric radii, while galaxies within the inner regions of the halo are sensitive to the dynamical state of their host group. Specifically, low-mass galaxies in unrelaxed groups show higher star-forming -- though no difference is detected when considering disc fractions. Together these findings help constrain the mechanisms at play in environmentally driven galaxy evolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".