4098 galaxy clusters to z∼ 0.6 in the Sloan Digital Sky Survey equatorial Stripe 82
Bibliographic record
Abstract
We present a catalogue of 4098 photometrically selected galaxy clusters with a median redshift 〈z〉= 0.32 in the 270 deg2‘Stripe 82’ region of the Sloan Digital Sky Survey (SDSS), covering the celestial equator in the Southern Galactic Cap (−50° < α < 59°, |δ| ≤ 1°.25). Owing to the multi-epoch SDSS coverage of this region, the ugriz photometry is ∼2 mag deeper than single scans within the main SDSS footprint. We exploit this to detect clusters of galaxies using an algorithm that searches for statistically significant overdensities of galaxies in a Voronoi tessellation of the projected sky. 32 per cent of the clusters have at least one member with a spectroscopic redshift from existing public data (SDSS Data Release 7, 2SLAQ and WiggleZ), and the remainder have a robust photometric redshift (accurate to ∼5–9 per cent at the median redshift of the sample). The weighted average of the member galaxies’ redshifts provides a reasonably accurate estimate of the cluster redshift. The cluster catalogue is publicly available for exploitation by the community to pursue a range of science objectives. In addition to the cluster catalogue, we provide a linked catalogue of 18 295 V≤ 21-mag quasar sightlines with impact parameters within ≤3 Mpc of the cluster cores selected from the catalogue of Veron-Cetty & Veron (2010). The background quasars cover 0.25 < z < 2, where Mg ii absorption-line systems associated with the clusters are detectable in optical spectra.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".