OmegaWINGS: OmegaCAM-VST observations of WINGS galaxy clusters
Bibliographic record
Abstract
Context. Wide-field observations targeting galaxy clusters at low redshift are complementary to field surveys and provide the local benchmark for detailed studies of the most massive haloes in the local Universe. The Wide-field Nearby Galaxy-cluster Survey (WINGS) is a wide-field multi-wavelength survey of X-ray selected clusters at z = 0.04–0.07. The original 34′ × 34′ WINGS field of view has now been extended to cover a 1 deg2 field with both photometry and spectroscopy. Aims. We present the Johnson B- and V-band OmegaCAM at the VST observations of 46 WINGS clusters together with the data reduction, data quality, and Sextractor photometric catalogues. Methods. The data reduction was carried out with a modified version of the ESO-MVM (also known as ALAMBIC) reduction package, adding a cross-talk correction, the gain harmonisation, and a control procedure for problematic CCDs. The stray-light component was corrected for by employing our own observations of populated stellar fields. Results. With a median seeing of 1″ in both bands, our 25-min exposures in each band typically reach the 50% completeness level at V = 23.1 mag. The quality of the astrometric and photometric accuracy has been verified by comparison with the 2MASS and SDSS astrometry, and SDSS and previous WINGS imaging. Star-to-galaxy separation and sky-subtraction procedure were tested comparing them with previous WINGS data. Conclusions. The Sextractor photometric catalogues are publicly available at the CDS and will be included in the next release of the WINGS database on the Virtual Observatory together with the OmegaCAM reduced images. These data form the basis for a large ongoing spectroscopic campaign with AAOmega at the AAT and are being employed for a variety of studies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".