<i>Gaia</i>reveals evidence for merged white dwarfs
Bibliographic record
Abstract
Abstract We use Gaia Data Release 2 to identify 13 928 white dwarfs (WDs) within 100 pc of the Sun. The exquisite astrometry from Gaia reveals for the first time a bifurcation in the observed WD sequence in both Gaia and the Sloan Digital Sky Survey (SDSS) passbands. The latter is easily explained by a helium atmosphere WD fraction of 36 per cent. However, the bifurcation in the Gaia colour–magnitude diagram depends on both the atmospheric composition and the mass distribution. We simulate theoretical colour–magnitude diagrams for single and binary WDs using a population synthesis approach and demonstrate that there is a significant contribution from relatively massive WDs that likely formed through mergers. These include WD remnants of main-sequence (blue stragglers) and post-main-sequence mergers. The mass distribution of the SDSS subsample, including the spectroscopically confirmed WDs, also shows this massive bump. This is the first direct detection of such a population in a volume-limited sample.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".