The age of the Galactic stellar halo from<i>Gaia</i>white dwarfs
Bibliographic record
Abstract
We use 156 044 white dwarf candidates with ≥5σ significant parallax measurements from the Gaia mission to measure the velocity dispersion of the Galactic disc; (σ U , σ V , σ W ) = (30.8,23.9, 20.0) km s -1 .We identify 142 objects that are inconsistent with disc membership at the >5σ level.This is the largest sample of field halo white dwarfs identified to date.We perform a detailed model atmosphere analysis using optical and near-infrared photometry and parallaxes to constrain the mass and cooling age of each white dwarf.The white dwarf cooling ages of our targets range from 7 Myr for J1657+2056 to 10.3 Gyr for J1049-7400.The latter provides a firm lower limit of 10.3 Gyr for the age of the inner halo based on the well-understood physics of white dwarfs.Including the pre-white dwarf evolutionary lifetimes, and limiting our sample to the recently formed white dwarfs with cooling ages of <500 Myr, we estimate an age of 10.9 ± 0.4 Gyr (internal errors only) for the Galactic inner halo.The coolest white dwarfs in our sample also give similar results.For example, J1049-7400 has a total age of 10.9-11.1 Gyr.Our age measurements are consistent with other measurements of the age of the inner halo, including the white dwarf based measurements of the globular clusters M4, NGC 6397, and 47 Tuc.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.000 | 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".