The physical properties of the dust in the RCW 120 H ii region as seen by<i>Herschel</i>
Bibliographic record
Abstract
Context. RCW 120 is a well-studied, nearby Galactic H ii region with ongoing star formation in its surroundings. Previous work has shown that it displays a bubble morphology at mid-infrared wavelengths, and has a massive layer of collected neutral material seen at sub-mm wavelengths. Given the well-defined photo-dissociation region (PDR) boundary and collected layer, it is an excellent laboratory to study the “collect and collapse” process of triggered star formation. Using Herschel Space Observatory data at 100, 160, 250, 350, and 500 μm, in combination with Spitzer and APEX-LABOCA data, we can for the first time map the entire spectral energy distribution of an H ii region at high angular resolution.Aims. We seek a better understanding of RCW 120 and its local environment by analysing its dust temperature distribution. Additionally, we wish to understand how the dust emissivity index, β, is related to the dust temperature.Methods. We determine dust temperatures in selected regions of the RCW 120 field by fitting their spectral energy distribution (SED), derived using aperture photometry. Additionally, we fit the SED extracted from a grid of positions to create a temperature map.Results. We find a gradient in dust temperature, ranging from 30 K in the interior of RCW 120, to ~20 K for the material collected in the PDR, to ~10 K toward local infrared dark clouds and cold filaments. There is an additional, hotter (~100 K) component to the dust emission that we do not investigate here. Our results suggest that RCW 120 is in the process of destroying the PDR delineating its bubble morphology. The leaked radiation from its interior may influence the creation of the next generation of stars. We find support for an anti-correlation between the fitted temperature and β, in rough agreement with what has been found previously. The extended wavelength coverage of the Herschel data greatly increases the reliability of this 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 | 0.001 | 0.001 |
| 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".