On the Spectral Evolution of Helium-atmosphere White Dwarfs Showing Traces of Hydrogen
Bibliographic record
Abstract
Abstract We present a detailed spectroscopic analysis of 115 helium-line (DB) and 28 cool, He-rich hydrogen-line (DA) white dwarfs based on atmosphere fits to optical spectroscopy and photometry. We find that 63% of our DB population show hydrogen lines, making them DBA stars. We also demonstrate the persistence of pure DB white dwarfs with no detectable hydrogen feature at low effective temperatures. Using state-of-the art envelope models, we next compute the total quantity of hydrogen, M H , that is contained in the outer convection zone as a function of effective temperature and atmospheric H/He ratio. We find that some ( T eff , M H ) pairs cannot physically exist as a homogeneously mixed structure; such a combination can only occur as stratified objects of the DA spectral type. On that basis, we show that the values of M H inferred for the bulk of the DBA stars are too large and incompatible with the convective dilution scenario. We also present evidence that the hydrogen abundances measured in DBA and cool, helium-rich white dwarfs cannot be globally accounted for by any kind of accretion mechanism onto a pure DB star. We suggest that cool, He-rich DA white dwarfs are most likely created by the convective mixing of a DA star with a thin hydrogen envelope; they are not cooled down DBAs. We finally explore several scenarios that could account for the presence of hydrogen in DBA stars.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".