Galaxy groups in various evolutionary stages
Bibliographic record
Abstract
Context. The formation process of galaxy groups is not yet fully understood. In particular, that of fossil groups (FGs) is still under debate. Due to the relative rarity of FGs, large samples of such objects are still missing. Aims. The present paper aims to analyse the properties of groups in various evolutionary stages (FGs, “almost” FGs, and non-FGs), and to increase the sample of FG candidates. Methods. We have spectroscopically observed galaxies in four groups and ten candidate FGs detected in the Canada France Hawaii Telescope Legacy Survey. We searched for substructures by applying the Serna–Gerbal dendrogram method to analyse the dynamical structure of each group. By applying the FIREFLY software to the continuum and PIPE_VIS to the emission lines, we derived the stellar population properties (e.g. number and age of starbursts, metallicity, fraction contributed by the burst to the luminosity) in various regions for each group. Results. A roughly continuous variation in properties is found between a group that is still building up (XCLASS 1330), a well-formed massive group (MCG+00-27-023), a dynamically complex non-FG (NGC 4065), and a near-FG (NGC 4104). We also optically confirm two FGs in the Canada France Hawaii Telescope Legacy Survey, but their X-ray luminosity is still unknown. Conclusions. We observe that the lower the mass of the substructure, the more recent the stellar population in the considered groups. We also show an apparent lack of high-mass substructures for low-metallicity systems. These results are consistent with the generally adopted model of energy transfer during interactions of the galaxies with the group and cluster potential wells. Furthermore, the fossil status of a group might be related to the large-scale environment. Therefore, studying the positions of non-FGs, near-FGs, and FGs within the cosmic web can provide insights into the process of how fossil systems come into being in the Universe.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".