Extreme star formation in the Milky Way: luminosity distributions of young stellar objects in W49A and W51
Bibliographic record
Abstract
We have compared the star-formation properties of the W49A and W51 regions by using far-infrared data from the Herschel infrared Galactic Plane Survey (Hi-GAL) and 850-|$\mu$|m observations from the James Clerk Maxwell Telescope (JCMT) to obtain luminosities and masses, respectively, of associated compact sources. The former are infrared luminosities from the catalogue of Elia et al., while the latter are from the JCMT Plane survey source catalogue as well as measurements from new data. The clump-mass distributions of the two regions are found to be consistent with each other, as are the clump-formation efficiency and star-formation efficiency analogues. However, the frequency distributions of the luminosities of the young stellar objects are significantly different. While the luminosity distribution in W51 is consistent with Galaxy-wide samples, that of W49A is top heavy. The differences are not dramatic and are concentrated in the central regions of W49A. However, they suggest that physical conditions there, which are comparable in part to those in extragalactic starbursts, are significantly affecting the star-formation properties or evolution of the dense clumps in the region.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".