The XMM Large-Scale Structure survey: an initial sample of galaxy groups and clusters to a redshift z < 0.6
Bibliographic record
Abstract
We present X-ray and optical spectroscopic observations of 12 galaxy groups and clusters identified within the X-ray Multi-Mirror (XMM) Large-Scale Structure (LSS) survey. Groups and clusters are selected as extended X-ray sources from a 3.5 deg2XMM image mosaic above a flux limit 8 × 10−15 erg s−1 cm−2 in the [0.5–2] keV energy band. Deep BVRI images and multi-object spectroscopy confirm each source as a galaxy concentration located within the redshift interval 0.29 < z < 0.56. We combine line-of-sight velocity dispersions with the X-ray properties of each structure computed from a two-dimensional surface brightness model and a single temperature fit to the XMM spectral data. The resulting distribution of X-ray luminosity, temperature and velocity dispersion indicate that the XMM—LSS survey is detecting low-mass clusters and galaxy groups to redshifts z < 0.6. Confirmed systems display little or no evidence for X-ray luminosity evolution at a given X-ray temperature compared to lower-redshift X-ray group and cluster samples. A more complete understanding of these trends will be possible with the compilation of a statistically complete sample of galaxy groups and clusters anticipated within the continuing XMM—LSS survey.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".