Candidate Hα emission and absorption line sources in the Galactic Bulge Survey
Bibliographic record
Abstract
We present a catalogue of candidate Hα emission and absorption line sources and blue objects in the Galactic Bulge Survey (GBS) region. We use a point source catalogue of the GBS fields (two strips of (l × b) = (6° × 1°) centred at b = 1| $_{.}^{\circ}$|5 above and below the Galactic Centre), covering the magnitude range 16 ≤ r΄ ≤ 22.5. We utilize (r΄ – i΄, r΄ – Hα) colour–colour diagrams to select Hα emission and absorption line candidates, and also identify blue objects (compared to field stars) using the r΄ – i΄ colour index. We identify 1337 Hα emission line candidates and 336 Hα absorption line candidates. These catalogues likely contain a plethora of sources, ranging from active (binary) stars, early-type emission line objects, cataclysmic variables (CVs) and low-mass X-ray binaries (LMXBs) to background active galactic nuclei (AGN). The 389 blue objects we identify are likely systems containing a compact object, such as CVs, planetary nebulae and LMXBs. Hot subluminous dwarfs (sdO/B stars) are also expected to be found as blue outliers. Cross-matching our outliers with the GBS X-ray catalogue yields 16 sources, including 7 (magnetic) CVs and 1 qLMXB candidate among the emission line candidates and 1 background AGN for the absorption line candidates. One of the blue outliers is a high-state AM CVn system. Spectroscopic observations combined with the multiwavelength coverage of this area, including X-ray, ultraviolet and (time-resolved) optical and infrared observations, can be used to further constrain the nature of individual sources.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".