AN EMPIRICAL MEASURE OF THE RATE OF WHITE DWARF COOLING IN 47 TUCANAE
Bibliographic record
Abstract
We present an empirical determination of the white dwarf cooling sequence in the globular cluster 47 Tucanae. Using spectral models, we determine temperatures for 887 objects from Wide Field Camera 3 data, as well as 292 objects from data taken with the Advanced Camera for Surveys. We make the assumption that the rate of white dwarf formation in the cluster is constant. Stellar evolution models are then used to determine the rate at which objects are leaving the main sequence, which must be the same as the rate at which objects are arriving on the white dwarf sequence in our field. The result is an empirically derived relation between temperature ( T eff ) and time ( t ) on the white dwarf cooling sequence. Comparing this result to theoretical cooling models, we find general agreement with the expected slopes between 20,000 K and 30,000 K and between 6000 K and 20,000 K, but the transition to the Mestel cooling rate of T eff ∝ t −0.4 is found to occur at hotter temperatures, and more abruptly than is predicted by any of these models.
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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 | 0.003 |
| 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".