<i>SWIFT</i>-BAT OBSERVATIONS OF THE RECENTLY DISCOVERED MAGNETAR SGR 0501+4516
Bibliographic record
Abstract
We present results on the soft gamma repeater (SGR) 0501+4516, discovered by the Swift Burst Alert Telescope (BAT) on 2008 August 22. More than 50 bursts were identified from this source, out of which 18 bursts had enough counts to carry out spectral analysis. We performed time-averaged spectral analysis on these 18 bursts using eight models, among which the cut-off power-law (PL) and the two-blackbody models provided the best fit in the 15–150 keV energy range. The cut-off PL model fit yields a mean photon index Γ CPL = 0.54 ± 0.11 and a cut-off energy E C = 19.1 ± 1.8 keV for the bursts. The mean hard and soft blackbody temperatures are found to be = 12.8 ± 0.7 keV and = 4.6 ± 0.5 keV, respectively, and are anti-correlated with the square of the radii of the hard and soft emitting regions ( and ) as ∝ kT −5.8 and ∝ kT −2.7 , respectively. The soft and hard component temperatures with different indices support the idea of two distinct emitting regions with the hard component corresponding to a smaller radius and the soft component corresponding to a larger radius, which further corroborate the idea of the propagation of extraordinary ( E ) and ordinary ( O ) mode photons across the photosphere, as predicted in the magnetar model. We notice strong burst fluence–duration correlation as well as hardness ratio–duration and hardness ratio–fluence anti-correlations for the SGR 0501+4516 bursts. The burst fluences range from ∼4.4 × 10 −9 ergs cm −2 to ∼2.7 × 10 −6 ergs cm −2 , consistent with those observed for typical short SGR bursts.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".