Radio variability from corotating interaction regions threading Wolf–Rayet winds
Bibliographic record
Abstract
ABSTRACT The structured winds of single massive stars can be classified into two broad groups: stochastic structure and organized structure. While the former is typically identified with clumping, the latter is typically associated with rotational modulations, particularly the paradigm of corotating interaction regions (CIRs). While CIRs have been explored extensively in the ultraviolet band, and moderately in the X-ray and optical, here we evaluate radio variability from CIR structures assuming free–free opacity in a dense wind. Our goal is to conduct a broad parameter study to assess the observational feasibility, and to this end, we adopt a phenomenological model for a CIR that threads an otherwise spherical wind. We find that under reasonable assumptions, it is possible to obtain radio variability at the 10 per cent level. The detailed structure of the folded light curve depends not only on the curvature of the CIR, the density contrast of the CIR relative to the wind, and viewing inclination, but also on wavelength. Comparing light curves at different wavelengths, we find that the amplitude can change, that there can be phase shifts in the waveform, and the entire waveform itself can change. These characterstics could be exploited to detect the presence of CIRs in dense, hot winds.
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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 | 0.002 |
| 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 | 0.001 | 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".