Substructure analysis of selected low-richness 2dFGRS clusters of galaxies
Bibliographic record
Abstract
Complementary one-, two- and three-dimensional tests for detecting the presence of substructure in clusters of galaxies are applied to recently obtained data from the 2dF Galaxy Redshift Survey. The sample of 25 clusters used in this study includes 16 clusters not previously investigated for substructure. Substructure is detected at or greater than the 99 per cent confidence level in at least one test for 21 of the 25 clusters studied here. From the results, it appears that low-richness clusters commonly contain subclusters participating in mergers. About half of the clusters have two or more components within 0.5 h−1 Mpc of the cluster centroid, and at least three clusters (Abell 1139, Abell 1663 and Abell S333) exhibit velocity–position characteristics consistent with the presence of possible cluster rotation, shear, or infall dynamics. The geometry of certain features is consistent with influence by the host supercluster environments. In general, our results support the hypothesis that low-richness clusters relax to structureless equilibrium states on very long dynamical time-scales (if at all).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".