ON THE EXISTENCE OF “RADIO THERMALLY ACTIVE” GALACTIC SUPERNOVA REMNANTS
Bibliographic record
Abstract
In this paper, we investigate the possibility of significant production of thermal bremsstrahlung radiation at radio continuum frequencies that could be linked to some Galactic supernova remnants (SNRs). The main targets for this investigation are SNRs expanding in high-density environments. There are several indicators of radio thermal bremsstrahlung radiation from SNRs, such as a flattening at higher frequencies and thermal absorption at lower frequencies intrinsic to an SNR. In this work, we discuss the radio continuum properties of three SNRs that are the best candidates for testing our hypothesis of significant thermal emission. In the case of SNRs IC 443 and 3C 391, thermal absorption has been previously detected. For IC 443, the contribution of thermal emission at 1 GHz, from our model fit is 3%–57%. It is similar to the estimate obtained from the thermal absorption properties (10%–40% at 1 GHz). In the case of the 3C 391 the conclusions are not so clear. The results from our model fit (thermal emission contribution of 10%–25% at 1 GHz) and results obtained from the low-frequency absorption (thermal contribution of 0.15%–7% at 1 GHz) do not overlap. For the SNR 3C 396 we suggest that if previously detected thermal absorption could be intrinsic to the SNR then the thermal emission (<47% at 1 GHz from our model fit) could be significant enough to shape the radio continuum spectrum at high frequencies. Polarization observations for these SNRs can constrain the strength of a thermal component. Reliable observations at low frequencies (<100 MHz) are needed as well as more data at high radio frequencies (>1 GHz), in order to make stronger conclusions about the existence of "radio thermally active" SNRs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".