A closer look at the binary content of NGC 1850
Bibliographic record
Abstract
ABSTRACT Studies of young clusters have shown that a large fraction of O-/early B-type stars are in binary systems, where the binary fraction increases with mass. These massive stars are present in clusters of a few Myr, but gradually disappear for older clusters. The lack of detailed studies of intermediate-age clusters has meant that almost no information is available on the multiplicity properties of stars with $M\lt 4\, {\rm M}_{\odot }$. In this study we present the first characterization of the binary content of NGC 1850, a 100 Myr-old massive star cluster in the Large Magellanic Cloud, relying on a VLT/MUSE multi-epoch spectroscopic campaign. By sampling stars down to M = 2.5 M⊙, we derive a close binary fraction of 24 ± 5 per cent in NGC 1850, in good agreement with the multiplicity frequency predicted for stars of this mass range. We also find a trend with stellar mass (magnitude), with higher mass (brighter) stars having higher binary fractions. We modelled the radial velocity curves of individual binaries using the joker and constrained the orbital properties of 27 systems, ∼17 per cent of all binaries with reliable radial velocities in NGC 1850. This study has brought to light a number of interesting objects, such as four binaries showing mass functions f(M) > 1.25 M⊙. One of these, star #47, has a peculiar spectrum, explainable with the presence of two discs in the system, around the visible star and the dark companion, which is a black hole candidate. These results confirm the importance and urgency of studying the binary content of clusters of any age.
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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".