Evolutionary Models for 15 Galactic Supernova Remnants with New Distances
Bibliographic record
Abstract
Abstract Recent studies using 21 cm H i line and 13CO line observations in the inner part of the Galaxy have resulted in new distances for 30 Galactic supernova remnants (SNRs). Of those remnants, 15 have observed X-ray spectra, for which shocked-gas temperatures and emission measures are measured. Here we apply spherically symmetric SNR evolution models to these 15 remnants to obtain estimates for ages, explosion energies, circumstellar medium densities and profiles (uniform or wind-type). From the distribution of ages we obtain a supernova birth rate and estimate incompleteness. The energies and densities can be well fit with log-normal distributions. The distribution of explosion energies is very similar to that of SNRs in the Large Magellanic Cloud (LMC), suggesting that SN explosions in the LMC and in the Galaxy are very similar. The density distribution has higher mean density for Galactic SNRs than for LMC SNRs by a factor ∼2.5.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".