The<i>Herschel</i>view of star formation in the Rosette molecular cloud under the influence of NGC 2244
Bibliographic record
Abstract
Context. The Rosette molecular cloud is promoted as the archetype of a triggered star-formation site. This is mainly due to its morphology, because the central OB cluster NGC 2244 has blown a circular-shaped cavity into the cloud and the expanding H II-region now interacts with the cloud. Aims. Studying the spatial distribution of the different evolutionary states of all star-forming sites in Rosette and investigating possible gradients of the dust temperature will help to test the “triggered star-formation” scenario in Rosette.Methods. We use continuum data obtained with the PACS (70 and 160 μm) and SPIRE instruments (250, 350, 500 μm) of the Herschel telescope during the science demonstration phase of HOBYS.Results. Three-color images of Rosette impressively show how the molecular gas is heated by the radiative impact of the NGC 2244 cluster. A clear negative temperature gradient and a positive density gradient (running from the H II-region/molecular cloud interface into the cloud) are detected. Studying the spatial distribution of the most massive dense cores (size scale 0.05 to 0.3 pc), we find an age-sequence (from more evolved to younger) with increasing distance to the cluster NGC 2244. No clear gradient is found for the clump (size-scale up to 1 pc) distribution.Conclusions. The existence of temperature and density gradients and the observed age-sequence imply that star formation in Rosette may indeed be influenced by the radiative impact of the central NGC 2244 cluster. A more complete overview of the prestellar and protostellar population in Rosette is required to obtain a firmer result.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".