The Isaac Newton Telescope Monitoring Survey of Local Group Dwarf Galaxies. VII. Long-period Variable Stars in the Nearest Starburst Dwarf Galaxy, IC 10
Bibliographic record
Abstract
Abstract To identify long-period variable (LPV) stars in IC 10—the nearest starburst galaxy of the Local Group—we conducted an optical monitoring survey using the 2.5 m Isaac Newton Telescope with the wide-field camera (WFC) in the i band and V band from 2015 to 2017. We created a photometric catalog for 53,579 stars within the area of CCD4 of WFC (∼0.07 deg2 corresponding to 13.5 kpc2 at the distance of IC 10), of which we classified 536 and 380 stars as LPV candidates, mostly asymptotic giant branch (AGBs) stars and red supergiants, within CCD4 and two half-light radii of IC 10, respectively. By comparing our output catalog to the catalogs from Pan-STARRS, Spitzer Space Telescope, Hubble Space Telescope (HST), and carbon stars from the Canada–France–Hawai’i Telescope survey, we determined the success of our detection method. We recovered ∼73% of Spitzer’s sources in our catalog and demonstrated that our survey successfully identified 43% of the variable stars found with Spitzer, and also retrieved 40% of the extremely dusty AGB stars among the Spitzer variables. In addition, we successfully identified ∼70% of HST variables in our catalog. Furthermore, we found all the confirmed LPVs that Gaia DR3 detected in IC 10 among our identified LPVs. This paper is the first in a series on IC 10, presenting the variable star survey methodology and the photometric catalog, available to the public through the Centre de Données Astronomiques de Strasbourg.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".