Image-Subtraction Photometry of Variable Stars in the Globular Clusters NGC 6388 and NGC 6441
Bibliographic record
Abstract
We have applied Alard's image-subtraction method (ISIS ver. 2.1) to the observations of the globular clusters NGC 6388 and NGC 6441 previously analyzed using standard photometric techniques (DAOPHOT and ALLFRAME). In this reanalysis of observations obtained at the Cerro Tololo Inter-American Observatory, besides recovering the variables previously detected on the basis of our ground-based images, we have also been able to recover most of the RR Lyrae variables previously detected only in the analysis of Hubble Space Telescope WFPC2 observations of the inner region of NGC 6441. In addition, we report five possible new variables not found in the analysis of the Hubble Space Telescope observations of NGC 6441. This dramatically illustrates the capabilities of image-subtraction techniques applied to ground-based data to recover variables in extremely crowded fields. We have also detected 12 new variables and 6 possible variables in NGC 6388 not found in our previous ground-based studies. The revised mean period for RR ab stars in NGC 6388 is 0.676 days, while the mean period of RR ab stars in NGC 6441 is unchanged at 0.759 days. These values are among the largest known for any Galactic globular cluster. Additional probable type II Cepheids were identified in NGC 6388, confirming its status as a metal-rich globular cluster rich in Cepheids.
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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 | 0.000 |
| 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".