The MACHO Project Sample of Galactic Bulge High‐Amplitude δ Scuti Stars: Pulsation Behavior and Stellar Properties
Bibliographic record
Abstract
We have detected 90 objects with periods and light-curve structures similar to those of field δ Scuti stars using the Massive Compact Halo Object (MACHO) Project database of Galactic bulge photometry. If we assume similar extinction values for all candidates and absolute magnitudes similar to those of other field high-amplitude δ Scuti stars (HADS), the majority of these objects lie in or near the Galactic bulge. At least two of these objects are likely foreground δ Scuti stars, one of which may be an evolved nonradial pulsator, similar to other evolved, disk-population δ Scuti stars. We have analyzed the light curves of these objects and find that they are similar to the light curves of field δ Scuti stars and the δ Scuti stars found by the Optical Gravitational Lens Experiment (OGLE). However, the amplitude distribution of these sources lies between those of low- and high-amplitude δ Scuti stars, which suggests that they may be an intermediate population. We have found nine double-mode HADS with frequency ratios ranging from 0.75 to 0.79, four probable double- and multiple-mode objects, and another four objects with marginal detections of secondary modes. The low frequencies (5-14 cycles day -1 ) and the observed period ratios of ~0.77 suggest that the majority of these objects are evolved stars pulsating in fundamental or first overtone radial modes.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".