On the environments and progenitors of supernova remnants associated with highly magnetized neutron stars
Bibliographic record
Abstract
Abstract The distinction between the high-magnetic field pulsars (HBPs, thought to be mainly rotation-powered) and magnetars (commonly believed to be powered by their super-strong magnetic fields) has been recently blurred with the discovery of magnetar-like activity from the HBP J1846–0258 in the SNR Kes 75. What determines the spin properties of a neutron star at birth and its manifestation as a magnetar-like or more classical pulsar is still not clear. Furthermore, although a few studies have suggested very massive progenitors for magnetars, there is currently no consensus on the progenitors of these objects. To address these questions, we examine their environments by studying or revisiting their securely associated SNRs. Our approach is to: 1) infer the mass of their progenitor stars through X-ray spectroscopic studies of the thermally emitting supernova ejecta, and 2) investigate the physical properties of their hosting SNRs and ambient conditions. We here highlight our detailed studies of two SNRs: G292.2–0.5, associated with the HBP J1119–6127, and Kes 73, associated with the AXP 1E 1841–045, and summarize the current view of the other (handful) HBP/magnetar-SNR associations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".