CFHT Legacy Ultraviolet Extension (CLUE): witnessing galaxy transformations up to 7âMpc from rich cluster cores
Bibliographic record
Abstract
Using the optical data from the Wide component of the Canada-France-Hawaii Telescope (CFHT) Legacy Survey, and new ultraviolet (UV) data from GALEX, we study the colours and specific star formation rates (SSFRs) of ∼ 100 galaxy clusters at 0.16 < z < 0.36, over areas extending out to radii of r∼ 7 Mpc. We use a multicolour, statistical background subtraction method to study the galaxy population at this radius; thus our results pertain to those galaxies which constitute an excess over the average field density. We find that the average SSFR and its distribution of the star-forming galaxies (with at z∼ 0.2 and at z∼ 0.3) have no measurable dependence on the clustercentric radius and are consistent with the field values. However, the fraction of galaxies with SFR above these thresholds, and the fraction of optically blue galaxies, are lower for the overdense galaxy population in the cluster outskirts compared with the average field value, at all stellar masses and at all radii out to at least 7 Mpc. Most interestingly, the fraction of blue galaxies that are forming stars at a rate below our UV detection limit is much higher in all radial bins around our cluster sample compared with the general field value. This is most noticeable for massive galaxies ; while almost all blue field galaxies of this mass have detectable star formation, this is true for less than 20 per cent of the blue cluster galaxies, even at 7 Mpc from the cluster centre. Our results support a scenario where galaxies are pre-processed in locally overdense regions in a way that reduces their SFR below our UV detection limit, but not to zero
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".