COOL WHITE DWARFS FOUND IN THE UKIRT INFRARED DEEP SKY SURVEY
Bibliographic record
Abstract
We present the results of a search for cool white dwarfs in the United Kingdom InfraRed Telescope (UKIRT) Infrared Deep Sky Survey (UKIDSS) Large Area Survey (LAS). The UKIDSS LAS photometry was paired with the Sloan Digital Sky Survey to identify cool hydrogen-rich white dwarf candidates by their neutral optical colors and blue near-infrared colors, as well as faint reduced proper motion magnitudes. Optical spectroscopy was obtained at Gemini Observatory and showed the majority of the candidates to be newly identified cool degenerates, with a small number of G- to K-type (sub)dwarf contaminants. Our initial search of 280 deg 2 of sky resulted in seven new white dwarfs with effective temperature T eff ≈ 6000 K. The current follow-up of 1400 deg 2 of sky has produced 13 new white dwarfs. Model fits to the photometry show that seven of the newly identified white dwarfs have 4120 K ⩽ T eff ⩽ 4480 K, and cooling ages between 7.3 Gyr and 8.7 Gyr; they have 40 km s −1 ⩽ v tan ⩽ 85 km s −1 and are likely to be thick disk 10–11 Gyr-old objects. The other half of the sample has 4610 K ⩽ T eff ⩽ 5260 K, cooling ages between 4.3 Gyr and 6.9 Gyr, and 60 km s −1 ⩽ v tan ⩽ 100 km s −1 . These are either thin disk remnants with unusually high velocities, or lower-mass remnants of thick disk or halo late-F or G stars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".