The XXL Survey
Bibliographic record
Abstract
Context.Distant galaxy clusters provide an effective laboratory in which to study galaxy evolution in dense environments and at early cosmic times. Aims.We aim to identify distant galaxy clusters as extended X-ray sources that are coincident with overdensities of characteristically bright galaxies. Methods.We used optical and near-infrared data from the Hyper Suprime-Cam and VISTA Deep Extragalactic Observations (VIDEO) surveys to identify distant galaxy clusters as overdensities of bright,zphot ≥ 0.8 galaxies associated with extended X-ray sources detected in the ultimate XMM extragalactic survey (XXL). Results.We identify a sample of 35 candidate clusters at 0.80 ≤ z ≤ 1.93 from an approximately 4.5 deg2sky area. This sample includes 15 newly discovered candidate clusters, ten previously detected but unconfirmed clusters, and ten spectroscopically confirmed clusters. Although these clusters host galaxy populations that display a wide variety of quenching levels, they exhibit well-defined relations between quenching, cluster-centric distance, and galaxy luminosity. The brightest cluster galaxies (BCGs) within our sample display colours that are consistent with a bimodal population composed of an old and red sub-sample together with a bluer, more diverse sub-sample. ConclusionsThe relation between galaxy masses and quenching seem to already be in place atz ∼ 1, although there is no significant variation in the quenching fraction with the cluster-centric radius. The BCG bimodality might be explained by the presence of a younger stellar component in some BCGs, but additional data are needed to confirm this scenario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.072 | 0.040 |
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".