The spectral variability of a sample of WC 9 stars on time-scales of days to weeks
Bibliographic record
Abstract
We present the results of a spectroscopic monitoring campaign of nine presumably single Wolf–Rayet (WR) stars, eight of type WC 9 and one WC 8d. We characterize their variability and search for clues to the mechanism responsible for the formation of dust in their wind. For seven out of eight WC 9s, we find a large-scale line-flux variability level of σ > 5–8 per cent. The only WC 8d star is variable at a level more comparable with those associated with wind clumping, σ = 2.2 per cent. The changes take place on a time-scale of days but in many cases, observing over longer time spans resulted in higher line-flux variability levels. The width of the substructures ranges from ∼150 to 300 km s−1, with the widest structures corresponding to stars with the highest variability amplitude. We searched for periodicities in integrated line quantities for C iii λ5696. Radial velocity changes are typically ∼20 km s−1 but never exceed 40 km s−1 and are anticorrelated with the skewness of the line, strongly suggesting that they do not correspond to a real movement of the star. No periodicity was found in these integrated quantities, except for WR 103. Therefore, a wind–wind collision in a close binary does not seem to be responsible for the short-term variability. We cannot, however, exclude that these stars are intermediate- to long-period binaries. We estimate that for periods up to a few years, the shock-cone resulting from wind collisions would be non-adiabatic and thus unstable. We suggest that this represents a viable mechanism to explain the spectroscopic variability.
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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 | 0.000 | 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".