Comparing Be Star Inclination Angles Determined from Hα Fitting and Gravitational Darkening
Bibliographic record
Abstract
Abstract Using a sample of 92 Galactic Be stars, we compare inclination angles (the angle between a star’s rotation axis and the line of sight) determined from Hα emission-line profile fitting to those determined by the spectroscopic signature of gravitational darkening. We find good agreement: 70% of the sample (64 out of 92 stars) is consistent with zero difference between the two methods using 1σ errors, and there is a strong linear correlation coefficient between the two methods of r = +0.63 ± 0.05. There is some evidence that the Hα profile fitting method overestimates the inclination angle for i ≲ 25°, perhaps due to the neglect of incoherent electron scattering on the Hα line widths, while the gravitational darkening method underestimates the inclination angle for i ≳ 70°, perhaps due to the neglect of disk radiative transfer effects on the optical spectrum. Overall, it is demonstrated that a single Hα spectrum of modest resolution and SNR can be used to extract a useful estimate for the inclination angle of an individual Be star. This allows equatorial rotation velocities for individual Be stars to be derived from v sin i measurements and will allow Be stars to be used to search for correlated spin axes in young, open clusters if unbiased (with respect to inclination) samples of Be stars are used.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".