Binary properties of the globular cluster 47 Tuc (NGC 104)
Bibliographic record
Abstract
Spectroscopic observations of binary stars in globular clusters are essential to shed light on the poorly constrained period, eccentricity, and mass ratio distributions and to develop an understanding of the formation of peculiar stellar objects. 47 Tuc (NGC 104) is one of the most massive Galactic globular clusters, with a large population of blue stragglers and with many predicted but as-yet elusive stellar-mass black holes. This makes it an exciting candidate for binary searches. We present a multi-epoch spectroscopic survey of 47 Tuc with the VLT/MUSE integral field spectrograph to determine radial velocity variations for 21 699 stars. We find a total binary fraction in the cluster of (2.4 ± 1.0)%, consistent with previous photometric estimates, and an increased binary fraction among blue straggler stars, approximately three times higher than the cluster average. We find very few binaries with periods below three days, and none with massive dark companions. A comparison with predictions from state-of-the-art models shows that the absence of such short-period binaries and of binaries with massive companions is surprising, highlighting the need to improve our understanding of stellar and dynamical evolution in binary systems.
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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) | 0.001 | 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".