The infrared and molecular environment surrounding the Wolf-Rayet star WR 130
Bibliographic record
Abstract
We present a study of the molecular CO gas and mid/far-infrared radiation arising from the environment surrounding the Wolf–Rayet (WR) star 130. We use the multiwavelength data to analyse the properties of the dense gas and dust, and its possible spatial correlation with that of young stellar objects (YSOs). We use 12CO J=1–0 data from the Five College Radio Astronomy Observatory survey as tracer of the molecular gas, and mid/far-infrared data from the recent Wide-Field Infrared Survey Explorer (WISE) and Herschel space surveys to study the dust continuum radiation and to identify a population of associated candidate YSOs. The spatial distribution of the molecular gas shows a ring-like structure very similar to that observed in the H i gas, and over the same velocity interval. The relative spatial distribution of the H i and CO components is consistent with a photodissociation region. We have identified and characterized four main and distinct molecular clouds that create this structure. Cold dust is coincident with the dense gas shown in the CO measurements. We have found several young stellar object candidates that lie along the regions with the highest gas column density, and suggest that they are spatially correlated with the shell. These are indicative of regions of star formation induced by the strong wind and ionization of the WR star.
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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) | 0.000 | 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".