The Gaia–WISE Extragalactic Astrometric Catalog
Bibliographic record
Abstract
The Gaia mission has detected a large number of active galactic nuclei (AGNs) and galaxies, but these objects must be identified among the thousandfold more numerous stars. Extant astrometric AGN catalogs do not have the uniform sky coverage required to detect and characterize the all-sky, low-multipole proper motion signals produced by the barycenter motion, gravitational waves, and cosmological effects. To remedy this, we present an all-sky sample of 567,721 AGNs in Gaia Data Release 1, selected using WISE two-color criteria. The catalog has fairly uniform sky coverage beyond the Galactic plane, with a mean density of 12.8 AGNs per square degree. The objects have magnitudes ranging from G = 8.8 down to Gaia's magnitude limit, G = 20.7. The catalog is approximately 50% complete but suffers from low stellar contamination, roughly 0.2%. We predict that the end-of-mission Gaia proper motions for this catalog will enable detection of the secular aberration drift to high significance (23σ) and will place an upper limit on the anisotropy of the Hubble expansion of about 2%.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 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) | 0.013 | 0.018 |
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".