<i>Hubble Space Telescope</i> Observations of the White Dwarf Cooling Sequence of M4
Bibliographic record
Abstract
We investigate in detail the white dwarf cooling sequence of the globular cluster Messier 4. In particular, we study the influence of various systematic uncertainties, both observational and theoretical, on the determination of the cluster age from the white dwarf cooling sequence. These include uncertainties in the distance to the cluster and the extinction along the line of sight, as well as the white dwarf mass, envelope, and core compositions and the white dwarf-main-sequence mass relation. We find that fitting to the full two-dimensional color-magnitude diagram offers a more robust method for age determination than the traditional method of fitting the one-dimensional white dwarf luminosity function. After taking into account the various uncertainties, we find a best-fit age of 12.1 Gyr, with a 95% lower limit of 10.3 Gyr. We also perform fits using two other sets of cooling models from the literature. The models of Chabrier et al. yield an encouragingly similar result, although the models of Salaris et al. do not provide as good a fit. Our results support our previous determination of a delay between the formation of the Galactic halo and the onset of star formation in the Galactic disk.
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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 | 0.002 | 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) | 0.002 | 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".