New evidences in IRDC G333.73 + 0.37: colliding filamentary clouds, hub-filament system, and embedded cores
Bibliographic record
Abstract
ABSTRACT To unravel the star formation process, we present a multi-scale and multi-wavelength study of the filamentary infrared dark cloud (IRDC) G333.73 + 0.37, which hosts previously known two H ii regions located at its center. Each H ii region is associated with a mid-infrared source, and is excited by a massive OB star. Two filamentary structures and a hub-filament system (HFS) associated with one H ii region are investigated in absorption using the Spitzer 8.0 μm image. The 13CO(J = 2–1) and C18O(J = 2–1) line data reveal two velocity components (around −35.5 and −33.5 km s−1) toward the IRDC, favouring the presence of two filamentary clouds at different velocities. Non-thermal (or turbulent) motions are depicted in the IRDC using the C18O line data. The spatial distribution of young stellar objects (YSOs) identified using the VVV near-infrared data traces star formation activities in the IRDC. Low-mass cores are identified toward both the H ii regions using the ALMA 1.38 mm continuum map. The VLT/NACO adaptive-optics L′-band images show the presence of at least three point-like sources and the absence of small-scale features in the inner 4000 AU around YSOs NIR31 and MIR 16 located toward the H ii regions. The H ii regions and groups of YSO are observed toward the central part of the IRDC, where the two filamentary clouds intersect. A scenario of cloud–cloud collision or converging flows in the IRDC seems to be applicable, which may explain star formation activities including HFS and massive stars.
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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 | 0.001 | 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".