On the detection of the progenitor of the type Ia supernova 2007on
Bibliographic record
Abstract
We present new Chandra X-ray observations and detailed astrometry of the field of the type Ia supernova 2007on, for which the detection of a likely progenitor in archival Chandra data was recently reported. No source is detected in the new Chandra images, taken six weeks after optical maximum. We calculate a 90–99 per cent probability that any X-ray source near the position of the supernova (SN) is fainter than in the pre-outburst images, depending on the choice of aperture, which supports the identification of the archival X-ray source with the SN. Detailed astrometry of the X-ray and new optical images, however, gives an offset between the SN and the measured X-ray source position of 1.15 ± 0.27 arcsec. Extensive simulations show that the probability of finding an offset of this magnitude is ∼1 per cent, equal to the (trial-corrected) probability of a chance alignment with any X-ray source in the field. This casts doubt on the identification of the X-ray source with the progenitor, although the scenario in which at least some of the observed X-rays are connected to the SN may be the least unlikely based on all available data. After a brief review of the auxiliary evidence, we conclude that only future X-ray observations can shed further light on the proposed connection between the X-ray source and the progenitor of SN 2007on, and thus whether an accreting white dwarf scenario is truly favoured for this SN Ia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".