WHITE DWARFS IN THE UKIRT INFRARED DEEP SKY SURVEY DATA RELEASE 9
Bibliographic record
Abstract
We have identified 8 to 10 new cool white dwarfs from the Large Area Survey (LAS) Data Release 9 of the United Kingdom InfraRed Telescope (UKIRT) Infrared Deep Sky Survey (UKIDSS). The data set was paired with the Sloan Digital Sky Survey to obtain proper motions and a broad ugrizYJHK wavelength coverage. Optical spectroscopic observations were secured at Gemini Observatory and confirm the degenerate status for eight of our targets. The final sample includes two additional white dwarf candidates with no spectroscopic observations. We rely on improved one-dimensional model atmospheres and new multi-dimensional simulations with CO5BOLD to review the stellar parameters of the published LAS white dwarf sample along with our additional discoveries. Most of the new objects possess very cool atmospheres with effective temperatures below 5000 K, including two pure-hydrogen remnants with a cooling age between 8.5 and 9.0 Gyr, and tangential velocities in the range 40 km s −1 ⩽ v tan ⩽ 60 km s −1 . They are likely thick disk 10–11 Gyr old objects. In addition, we find a resolved double degenerate system with v tan ∼ 155 km s −1 and a cooling age between 3.0 and 5.0 Gyr. These white dwarfs could be disk remnants with a very high velocity or former halo G stars. We also compare the LAS sample with earlier studies of very cool degenerates and observe a similar deficit of helium-dominated atmospheres in the range 5000 < T eff (K) < 6000. We review the possible explanations for the spectral evolution from helium-dominated toward hydrogen-rich atmospheres at low temperatures.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".