ATOMS: ALMA three-millimeter observations of massive star-forming regions – XIX. The origin of SiO emission
Bibliographic record
Abstract
ABSTRACT The production of silicon monoxide (SiO) can be considered as a fingerprint of shock interaction. In this work, we use high-sensitivity observations of the SiO (2–1) and H$^{13}$CO$^{+}$ (1–0) emission to investigate the broad and narrow SiO emission towards 146 massive star-forming regions in the ATOMS (ALMA Three-millimeter Observations of Massive Star-forming regions) survey. We detected SiO emission in 136 regions and distinguished broad and narrow components across the extension of 118 sources (including 58 UC H ii regions) with an average angular resolution of 2.5 arcsec. The derived SiO luminosity ($L_{\rm SiO}$) across the whole sample shows that the majority of $L_{\rm SiO}$ (above 66 per cent) can be attributed to broad SiO, indicating its association with strong outflows. The comparison of the ALMA SiO images with the filamentary skeletons identified from H$^{13}$CO$^{+}$ and in the infrared data (at 4.5, 8, and 24 μm), further confirms that most SiO emission originates from outflows. However, note that for nine sources in our sample, the observed SiO emission may be generated by expanding UC H ii regions. There is a moderate positive correlation between the bolometric luminosity ($L_{\rm bol}$) and $L_{\rm SiO}$ for both components (narrow and broad). The UC H ii sources show a weaker positive correlation between $L_{\rm bol}$ and $L_{\rm SiO}$ and higher $L_{\rm SiO}$ compared to the sources without UC H ii regions. These results imply that the SiO emission from UC H ii sources might be affected by UV-photochemistry induced by UC H ii regions.
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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 | 0.000 |
| 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".