Bibliographic record
Abstract
We study gamma-ray supernova remnant (SNR) W49B and its environment using recent radio and infrared data. Spitzer Infrared Spectrograph low resolution data of W49B shows shocked excitation lines of H 2 (0,0) S (0)– S (7) from the SNR–molecular cloud interaction. The H 2 gas is composed of two components with temperatures of ∼260 K and ∼1060 K, respectively. Various spectral lines from atomic and ionic particles are detected toward W49B. We suggest that the ionic phase has an electron density of ∼500 cm −3 and a temperature of ∼10 4 K by the spectral line diagnoses. The mid- and far-infrared data from MSX , Spitzer , and Herschel reveal a 151 ± 20 K hot dust component with a mass of 7.5 ± 6.6 × 10 −4 M ☉ and a 45 ± 4 K warm dust component with a mass of 6.4 ± 3.2 M ☉ . The hot dust is likely from materials swept up by the shock of W49B. The warm dust may possibly originate from the evaporation of clouds interacting with W49B. We build the H i absorption spectra of W49B and four nearby H ii regions (W49A, G42.90+0.58, G42.43–0.26, and G43.19–0.53) and study the relation between W49B and the surrounding molecular clouds by employing the 2.12 μm infrared and CO data. We therefore obtain a kinematic distance of ∼10 kpc for W49B and suggest that the remnant is likely associated with the CO cloud at about 40 km s −1 .
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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 | 0.001 |
| 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".