A high-frequency radio continuum study of massive young stellar objects
Bibliographic record
Abstract
We present high-resolution observations made with the Very Large Array (VLA) in its A configuration at frequencies between 5 and 43 GHz of a sample of five massive young stellar objects (YSOs): Lk Hα101, NGC 2024-IRS2, S106-IR, W75N and S140-IRS1. The resolution varied from 0.04 arcsec (at 43 GHz) to 0.5 arcsec (at 5 GHz), corresponding to a linear resolution as high as 17 au for our nearest source. A MERLIN observation of S106-IR at 23 GHz with 0.03-arcsec resolution is also presented. S106-IR and S140-IRS1 are elongated at 43 GHz perpendicular to their large-scale bipolar outflows. This confirms the equatorial wind picture for these sources seen previously in MERLIN 5-GHz observations. The other sources are marginally resolved at 43 GHz. The spectral indices we derive for the sources in our sample range from +0.2 to +0.8, generally consistent with ionized stellar winds. We have modelled our sources as uniform, isothermal spherical winds, with Lk Hα101 and NGC 2024-IRS2 yielding the best fits. However, in all cases our fits give wind temperatures of only 2000–5000 K, much less than the effective temperatures of main-sequence stars of the same luminosity, a result which is likely due to the clumpy nature of the 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 | 0.000 |
| 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 | 0.000 | 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".