The VAST Survey – III. The multiplicity of A-type stars within 75 pc
Bibliographic record
Abstract
With a combination of adaptive optics imaging and a multi-epoch common proper motion search, we have conducted a large volume-limited (D $\le$ 75 pc) multiplicity survey of A-type stars, sensitive to companions beyond 30 au. The sample for the Volume-limited A-STar (VAST) survey consists of 435 A-type stars: 363 stars were observed with adaptive optics, 228 stars were searched for wide common proper motion companions and 156 stars were measured with both techniques. The projected separation coverage of the VAST survey extends from 30 to 45,000 au. A total of 137 stellar companions were resolved, including 64 new detections from the VAST survey, and the companion star fraction, projected separation distribution and mass ratio distribution were measured. The separation distribution forms a log-normal distribution similar to the solar-type binary distribution, but with a peak shifted to a significantly wider value of 387 (+132,-98) au. Integrating the fit to the distribution over the 30 to 10,000 au observed range, the companion star fraction for A-type stars is estimated as 33.8%+-2.6%. The mass ratio distribution of closer (<125 au) binaries is distinct from that of wider systems, with a flat distribution for close systems and a distribution that tends towards smaller mass ratios for wider binaries. Combining this result with previous spectroscopic surveys of A-type stars gives an estimate of the total companion star fraction of 68.9%+-7.0%. The most complete assessment of higher order multiples was estimated from the 156-star subset of the VAST sample with both adaptive optics and common proper motion measurements, combined with a literature search for companions, yielding a lower limit on the frequency of single, binary, triple, quadruple and quintuple A-type star systems of 56.4 (-4.0,+3.8), 32.1 (-3.5,+3.9), 9.0 (-1.8,+2.8), 1.9 (-0.6,+1.8) and 0.6 (-0.2,+1.4) per cent, respectively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".