Photometric Variability among the Brightest Asymptotic Giant Branch Stars near the Center of M32
Bibliographic record
Abstract
Deep K ' images with 0 1 angular resolution, obtained with Altair+NIRI on Gemini North, are used to investigate photometric variability among the brightest asymptotic giant branch (AGB) stars in the central regions of M32. On the basis of a comparison with brightnesses obtained from the K -band data discussed by Davidge et al., it is concluded that (1) at least 60% of bright AGB stars near the center of M32 are photometrically variable, and (2) the amplitudes of the light variations are similar to those of long-period variables in the Galactic bulge. We do not find evidence for a population of large-amplitude variables, such as those detected by IRAS in the Galactic bulge. The technique discussed here may prove useful for conducting an initial reconnaisance of photometric variability among AGB stars in spheroids in the Virgo Cluster and beyond, where the required long exposure times may restrict observations to only a few epochs.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".