Bibliographic record
Abstract
Context. The XXL Survey is the largest homogeneous and contiguous survey carried out with XMM-Newton. Covering an area of 50 deg2 distributed over two fields, it primarily investigates the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. Aims. Given its depth and sky coverage, XXL is particularly suited to systematically unveiling the clustering of X-ray clusters and to identifying superstructures in a homogeneous X-ray sample down to the typical mass scale of a local massive cluster. Methods. A friends-of-friends algorithm in three-dimensional physical space was run to identify large-scale structures. In this paper we report the discovery of the highest redshift supercluster of galaxies found in the XXL Survey. We describe the X-ray properties of the clusters members of the structure and the optical follow-up. Results. The newly discovered supercluster is composed of six clusters of galaxies at a median redshift z ~ 0.43 and distributed across ~30′× 15′ (10 × 5 Mpc) on the sky. This structure is very compact with all the clusters residing in one XMM pointing; for this reason this is the first supercluster discovered with the XXL Survey. Photometric redshifts from the CFHTLS (Canada-France-Hawaii Telescope Legacy Survey) data release T0007 placed the supercluster at an approximate redshift of zphot ~ 0.45; subsequent spectroscopic follow-up with WHT (William Herschel Telescope) and NTT (New Technology Telescope) confirmed a median redshift of z ~ 0.43. An estimate of the X-ray mass and luminosity of this supercluster returns values of 1.7 × 1015 M⊙ and of 1.68 × 1044 erg s-1, respectively, and a total gas mass of Mgas = 9.3 × 1013 M⊙. These values put XLSSC-e at the average mass range of superclusters; its appearance, with two members of equal size, is quite unusual with respect to other superclusters and provides a unique view of the formation process of a massive structure.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.080 | 0.047 |
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".