A Deficit of Massive White Dwarfs in Gaia Astrometric Binaries
Bibliographic record
Abstract
Abstract The third data release of Gaia introduced a large catalog of astrometric binaries, out of which about 3200 are likely main-sequence stars with a white dwarf (WD) companion. These binaries are typically found with orbital separations of ∼1 au, a separation range that was largely unexplored due to observational challenges. Such systems are likely to have undergone a phase of stable mass transfer while the WD progenitor was on the asymptotic giant branch. Here we study the WD mass distribution of a volume-complete sample of binaries with K/M dwarf primaries and orbital separations of ∼1 au. We find that the number of massive WDs relative to the total number of WDs in these systems is smaller by an order of magnitude compared to their occurrence among single WDs in the field. One possible reason can be an implicit selection of the WD mass range if these are indeed post-stable-mass-transfer systems. Another reason can be the lack of merger products in our sample compared to the field, due to the relatively tight orbital separations of these systems. In addition, we find that about 14% of these systems have distant tertiary companions within 1 pc.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".