The GeMS/GSAOI Galactic Globular Cluster Survey (G4CS). II. Characterization of 47 Tuc with Bayesian Statistics
Bibliographic record
Abstract
Abstract We present a photometric analysis of globular cluster 47 Tuc (NGC 104) using near-IR imaging data from the GeMS/GSAOI Galactic Globular Cluster Survey (G4CS), which is in operation at Gemini-South telescope. Our survey is designed to obtain AO-assisted deep imaging with near diffraction-limited spatial resolution of the central fields of Milky Way globular clusters. The G4CS near-IR photometry was combined with an optical photometry catalog that was obtained from Hubble Space Telescope survey data to produce a high-quality color–magnitude diagram that reaches down to K s ≈ 21 Vega mag. We used the software suite BASE-9, which uses an adaptive Metropolis sampling algorithm to perform a Markov chain Monte Carlo Bayesian analysis, and obtained probability distributions and precise estimates for the age, distance, and extinction cluster parameters. Our best estimate for the age of 47 Tuc is 12.42 − 0.05 + 0.05 ± 0.08 Gyr and our true distance modulus estimate is (m−M)0 = 13.250 − 0.003 + 0.003 ± 0.028 mag, which are in tight agreement with previous studies using Gaia DR2 parallax and detached eclipsing binaries.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 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".