<i>Gaia</i>Data Release 3
Bibliographic record
Abstract
Context.TheGaiaDR3 catalogue contains, for the first time, about 800 000 solutions with either orbital elements or trend parameters for astrometric, spectroscopic, and eclipsing binaries, and combinations of these three. Aims.With this paper, we aim to illustrate the huge potential of this large non-single-star catalogue. Methods.Using the orbital solutions and models of the binaries, we have built a catalogue of tens of thousands of stellar masses or lower limits thereof, some with consistent flux ratios. Properties concerning the completeness of the binary catalogues are discussed, statistical features of the orbital elements are explained, and a comparison with other catalogues is performed. Results.Illustrative applications are proposed for binaries across the Hertzsprung-Russell Diagram (HRD). Binarity is studied in the giant branch and a search for genuine spectroscopic binaries among long-period variables is performed. The discovery of new EL CVn systems illustrates the potential of combining variability and binarity catalogues. Potential compact object companions are presented, mainly white dwarf companions or double degenerates, but one candidate neutron star is also found. Towards the bottom of the main sequence, the orbits of previously suspected binary ultracool dwarfs are determined and new candidate binaries are discovered. The long awaited contribution ofGaiato the analysis of the substellar regime shows the brown dwarf desert around solar-type stars using true rather than minimum masses, and provides new important constraints on the occurrence rates of substellar companions to M dwarfs. Several dozen new exoplanets are proposed, including two with validated orbital solutions and one super-Jupiter orbiting a white dwarf, all being candidates requiring confirmation. Besides binarity, higher order multiple systems are also found. Conclusions.By increasing the number of known binary orbits by more than one order of magnitude,GaiaDR3 will provide a rich reservoir of dynamical masses and an important contribution to the analysis of stellar multiplicity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.049 |
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".