WISE × SuperCOSMOS PHOTOMETRIC REDSHIFT CATALOG: 20 MILLION GALAXIES OVER 3π STERADIANS
Bibliographic record
Abstract
ABSTRACT We cross-match the two currently largest all-sky photometric catalogs—mid-infrared Wide-field Infrared Survey Explorer and SuperCOSMOS scans of UKST/POSS-II photographic plates—to obtain a new galaxy sample that covers 3 π steradians. In order to characterize and purify the extragalactic data set, we use external GAMA and Sloan Digital Sky Survey spectroscopic information to define quasar and star loci in multicolor space, aiding the removal of contamination from our extended source catalog. After appropriate data cleaning, we obtain a deep wide-angle galaxy sample that is approximately 95% pure and 90% complete at high Galactic latitudes. The catalog contains close to 20 million galaxies over almost 70% of the sky, outside the Zone of Avoidance and other confused regions, with a mean surface density of more than 650 sources per square degree. Using multiwavelength information from two optical and two mid-IR photometric bands, we derive photometric redshifts for all the galaxies in the catalog, using the ANN z framework trained on the final GAMA-II spectroscopic data. Our sample has a median redshift of , with a broad reaching up to z > 0.4. The photometric redshifts have a mean bias of , a normalized scatter of σ z = 0.033, and less than 3% outliers beyond 3 σ z . Comparison with external data sets shows no significant variation of photo- z quality with sky position. Together with the overall statistics, we also provide a more detailed analysis of photometric redshift accuracy as a function of magnitudes and colors. The final catalog is appropriate for “all-sky” three-dimensional (3D) cosmology to unprecedented depths, in particular through cross-correlations with other large-area surveys. It should also be useful for source preselection and identification in forthcoming surveys, such as TAIPAN or WALLABY.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 teacher head, 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".