The evolution of carbon-polluted white dwarfs at low effective temperatures
Bibliographic record
Abstract
ABSTRACT Taking advantage of the Gaia Data Release 2, recent studies have revisited the evolution of carbon-polluted white dwarfs (DQs) across a large range of effective temperatures. These analyses have clearly confirmed the existence of two distinct DQ evolutionary sequences: one with normal-mass white dwarfs and one with heavily polluted and generally more massive objects. The first sequence is thought to result from the dredge-up of carbon from the core, while the second could at least partially be made of descendants of hot DQs. However, the evolution of carbon-polluted white dwarfs below 6500 K remains unexplored, mainly due to the theoretical difficulties associated with modelling their dense atmospheres. In this work, we present a detailed star-by-star analysis of cool carbon-polluted white dwarfs. Our recently improved atmosphere models allow us to obtain good fits to most objects, including very cool DQpec white dwarfs with strongly shifted C2 molecular bands. We show that cool carbon-polluted white dwarfs keep following the two distinct evolutionary tracks previously identified at higher temperatures. We also find that most DQ white dwarfs transform into DQpec when their photospheric densities exceed ${\approx}0.15\, {\textrm{g\,cm}}^{-3}$. However, we identify stars for which the DQ→DQpec transition occurs at lower photospheric densities, possibly due to the presence of a strong magnetic field.
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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 | 0.001 |
| 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) | 0.000 | 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".