Preprint typeset using L ATEX style emulateapj v. 10/09/06 XMM-Newton, Chandra, AND CGPS OBSERVATIONS OF THE SUPERNOVA REMNANTS G85.4+0.7 AND G85.9−0.6
Bibliographic record
Abstract
We present an XMM-Newton detection of two low radio surface brightness SNRs, G85.4+0.7 and G85.9−0.6, discovered with the Canadian Galactic Plane Survey (CGPS). High-resolution XMM-Newton images revealing the morphology of the diffuse emission, as well as discrete point sources, are presented and correlated with radio and Chandra images. The new data also permit a spectroscopic analysis of the diffuse emission regions, and a spectroscopic and timing analysis of the point sources. Distances have been determined from H I and CO data to be 3.5 ± 1.0 kpc for SNR G85.4+0.7 and 4.8 ± 1.6 kpc for SNR G85.9−0.6. The SNR G85.4+0.7 is found to have a temperature of ∼ 12 −13 MK and a 0.5–2.5 keV luminosity of ∼ 1 − 4 × 10 33 D 2 3.5 erg/s (where D3.5 is the distance in units of 3.5 kpc), with an electron density ne of ∼ 0.07 − 0.16(fD3.5) −1/2 cm −3 (where f is the volume filling factor), and a shock age of ∼ 9 − 49(fD3.5) 1/2 kyr. The SNR G85.9−0.6 is found to have a temperature of ∼ 15 −19 MK and a 0.5–2.5 keV luminosity of ∼ 1 − 4 × 10 34 D 2 4.8 erg/s (where D4.8 is the distance in units of 4.8 kpc), with an electron density ne of ∼ 0.04 − 0.10(fD4.8) −1/2 cm −3 and a shock age of ∼ 12 − 42(fD4.8) 1/2 kyr. Based on the data presented here, none of the point sources appears to be the neutron star associated with either SNR.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.871 | 0.850 |
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".