NIR counterparts to ULXs (III): completing the photometric survey and selected spectroscopic results★
Bibliographic record
Abstract
ABSTRACT We present results from the remaining sources in our search for near-infrared (NIR) candidate counterparts to ultraluminous X-ray sources (ULXs) within ≃10 Mpc. We observed 23 ULXs in 15 galaxies and detected NIR candidate counterparts to 6 of them. Two of these have an absolute magnitude consistent with a single red supergiant (RSG). Three counterparts are too bright for an RSG and spatially extended, and thus we classify them as stellar clusters. The other candidate is too faint for an RSG. Additionally, we present the results of our NIR spectroscopic follow-up of five sources: four originally classified as RSG and one as a stellar cluster on the basis of previous photometry. The stellar cluster candidate is actually a nebula. Of the four RSG candidates, one source has a broad H α emission line redshifted by ∼z = 1, making it a background active galactic nucleus (AGN). Two other sources show stellar spectra consistent with them being RSGs. The final RSG candidate is too faint to classify, but does not show strong (nebular) emission lines in its spectrum. After our search for NIR counterparts to 113 ULXs, where we detected a candidate counterpart for 38 ULXs, we have spectroscopically confirmed the nature of 12: 5 sources are nebulae, 1 source is not classified, 1 source is an AGN, and 5 are RSGs. These possible five ULX–RSG binary systems would constitute ${\simeq} (4 \pm 2){{\ \rm per\ cent}}$ of the observed ULXs, a fraction almost four times larger than what was predicted by binary evolution simulations.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".