Bibliographic record
Abstract
Abstract An ultraviolet (UV) survey of M31 has been carried out during 2017–19 with the Ultra-Violet Imaging Telescope (UVIT) instrument on board the AstroSat Observatory. Here we match the M31 UVIT source catalog with the Chandra source catalog. We find 67 UVIT/Chandra sources detected in a varying number of UV and X-ray bands. The UV and X-ray photometry is analyzed using power-law and blackbody models. The X-ray types include 15 low-mass X-ray binaries (LMXBs) and five active galactic nuclei. Crossmatches with catalogs of stars, clusters, and other source types yield the following: 20 of the UVIT/Chandra sources match with M31 globular clusters, and nine with foreground stars. Three more globular clusters and two more foreground stars are consistent with the UVIT source positions although outside the Chandra match radius of 1″. The UV emission of the UVIT/Chandra sources associated with globular clusters is consistent with emission from blue horizontal branch stars rather than from the X-ray source. The LMXBs in globular clusters are among the most luminous globular clusters in M31. Comparison with stellar evolutionary tracks shows that the UVIT/Chandra sources with high UV blackbody temperatures are consistent with massive (10–30 M ⊙) stars in M31.
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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 | 0.003 | 0.002 |
| 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".