Filaments and ridges in Vela C revealed by<i>Herschel</i>: from low-mass to high-mass star-forming sites
Bibliographic record
Abstract
We present the first Herschel PACS and SPIRE results of the Vela C molecular complex in the far-infrared and submillimetre regimes at 70, 160, 250, 350, and 500 μm, spanning the peak of emission of cold prestellar or protostellar cores. Column density and multi-resolution analysis (MRA) differentiates the Vela C complex into five distinct sub-regions. Each sub-region displays differences in their column density and temperature probability distribution functions (PDFs), in particular, the PDFs of the “Centre-Ridge” and “South-Nest” sub-regions appear in stark contrast to each other. The Centre-Ridge displays a bimodal temperature PDF representative of hot gas surrounding the HII region RCW 36 and the cold neighbouring filaments, whilst the South-Nest is dominated by cold filamentary structure. The column density PDF of the Centre-Ridge is flatter than the South-Nest, with a high column density tail, consistent with formation through large-scale flows, and regulation by self-gravity. At small to intermediate scales MRA indicates the Centre-Ridge to be twice as concentrated as the South-Nest, whilst on larger scales, a greater portion of the gas in the South-Nest is dominated by turbulence than in the Centre-Ridge. In Vela C, high-mass stars appear to be preferentially forming in ridges, i.e., dominant high column density filaments.
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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 | 0.001 | 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) | 0.001 | 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".