<i>XMM-Newton</i> campaign on the ultraluminous X-ray source NGC 247 ULX-1: outflows
Bibliographic record
Abstract
ABSTRACT Most ultraluminous X-ray sources (ULXs) are believed to be powered by super-Eddington accreting neutron stars and, perhaps, black holes. Above the Eddington rate the disc is expected to thicken and to launch powerful winds through radiation pressure. Winds have been recently discovered in several ULXs. However, it is yet unclear whether the thickening of the disc or the wind variability causes the switch between the classical soft and supersoft states observed in some ULXs. In order to understand such phenomenology and the overall super-Eddington mechanism, we undertook a large (800 ks) observing campaign with XMM-Newton to study NGC 247 ULX-1, which shifts between a supersoft and classical soft ULX state. The new observations show unambiguous evidence of a wind in the form of emission and absorption lines from highly ionized ionic species, with the latter indicating a mildly relativistic outflow (−0.17c) in line with the detections in other ULXs. Strong dipping activity is observed in the light curve and primarily during the brightest observations, which is typical among soft ULXs, and indicates a close relationship between the accretion rate and the appearance of the dips. The latter is likely due to a thickening of the disc scale height and the wind as shown by a progressively increasing blueshift in the spectral lines.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".