Bibliographic record
Abstract
Abstract Missing from the usual considerations of nuclear burning white dwarfs as Type Ia supernovae progenitors are systems with very higher mass transfer rates, where more material than is needed for steady burning accretes on the white dwarf. This will expand the photosphere of the white dwarf, causing it to emit at longer wavelengths. Thus, we propose the name ultra-soft source (USS) for these objects. We present a VLT/FLAMES survey looking for USSs in the SMC, selected to be bright in the far UV and with blue far UV-V colors. While we find some unusual objects, and recover known planetary nebulae and WR stars, we detect no objects with strong He II lines, which should be a signature of USSs. This null result either puts an upper limit on the number of USSs in the SMC, or shows that we do not understand what the optical spectra of such objects will look like. We also discuss the unusual LMC [WN] planetary nebula LMC N66 as a possible example of a USS. It has a luminosity consistent with that expected, and its spectra show incompletely CNO-processed material — strong helium lines, some hydrogen, enhanced nitrogen and depleted carbon. It also shows periodic outbursts. USSs may resemble N66 in quiescence. However, it lacks a FUV excess, contrary to our predictions.
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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 | 0.001 | 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) | 0.002 | 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".