The Discordance of Mass‐Loss Estimates for Galactic O‐Type Stars
Bibliographic record
Abstract
We have determined accurate values of the product of the mass-loss rate and the ion fraction of P +4 , q (P +4 ), for a sample of 40 Galactic O-type stars by fitting stellar wind profiles to observations of the P V resonance doublet obtained with FUSE , ORFEUS BEFS, and Copernicus . When P +4 is the dominant ion in the wind [i.e., 0.5 ≲ q (P +4 ) ≤ 1], q (P +4 ) approximates the mass-loss rate to within a factor of ≲2. Theory predicts that P +4 is the dominant ion in the winds of O7-O9.7 stars, although an empirical estimator suggests that the range O4-O7 may be more appropriate. However, we find that the mass-loss rates obtained from P V wind profiles are systematically smaller than those obtained from fits to Hα emission profiles or radio free-free emission by median factors of ~130 (if P +4 is dominant between O7 and O9.7) or ~20 (if P +4 is dominant between O4 and O7). These discordant measurements can be reconciled if the winds of O stars in the relevant temperature range are strongly clumped on small spatial scales. We use a simplified two-component model to investigate the volume filling factors of the denser regions. This clumping implies that mass-loss rates determined from "ρ 2 " diagnostics have been systematically overestimated by factors of 10 or more, at least for a subset of O stars. Reductions in the mass-loss rates of this size have important implications for the evolution of massive stars and quantitative estimates of the feedback that hot-star winds provide to their interstellar environments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".