FAR-INFRARED LUMINOUS SUPERNOVA REMNANT Kes 17
Bibliographic record
Abstract
We present the results of infrared (IR; 2.5--160 um) observations of the supernova remnant (SNR) Kes 17 based on the data obtained with the AKARI and Spitzer satellites. We first detect bright continuum emission of its western shell in the mid- and far-IR wavebands together with its near-IR molecular line emission. We also detect hidden mid-IR emission of its southern shell after subtraction of the background emission in this region. The far-IR luminosity of the western shell is ~ 8100 L_sun, which makes Kes 17 one of the few SNRs of significant far-IR emission. The fittings of the spectral energy distribution indicate the existence of two dust components: ~ 79 K (hot) and ~ 27 K (cold) corresponding to the dust mass of ~ 6.2x10^{-4} M_sun and ~ 6.7 M_sun, respectively. We suggest that the hot component represents the dust emission of the material swept up by the SNR to its western and southern boundaries, compatible with the distribution of radio continuum emission overlapping the mid-IR emission in the western and southern shells. The existence of hot (~ 2,000 K), shocked dense molecular gas revealed by the near-IR molecular line emission in the western shell, on the other hand, suggests that the cold dust component represents the dust emission related to the interaction between the SNR and nearby molecular gas. The excitation conditions of the molecular gas appear to be consistent with those from shocked, clumpy admixture gas of different temperatures. We discuss three possibilities for the origin of the bright far-IR emission of the cold dust in the western shell: the emission of dust in the inter-clump medium of shocked molecular clouds, the emission of dust in evaporating flows of molecular clouds engulfed by hot gas, and the emission of dust of nearby molecular clouds illuminated by radiative shocks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".