A new kinematic model of the Galaxy: analysis of the stellar velocity field from <i>Gaia</i> Data Release 3
Bibliographic record
Abstract
ABSTRACT This work presents the results of a kinematic analysis of the Galaxy that uses a new model as applied to the newest available Gaia data. We carry out the Taylor decomposition of the velocity field up to second order for 18 million high luminosity stars (i.e. OBAF-type stars, giants, and subgiants) from the Gaia DR3 data. We determine the components of mean stellar velocities and their first and second partial derivatives (relative to cylindrical coordinates) for more than 28 thousand points in the plane of our Galaxy. We estimate Oort’s constants A, B, C, and K and other kinematics parameters and map them as a function of Galactocentric coordinates. The values found confirm the results of our previous works and are in excellent agreement with those obtained by other authors in the solar neighbourhood. In addition, the introduction of second order partial derivatives of the stellar velocity field allows us to determine the values of the vertical gradient of the Galaxy azimuthal, radial, and vertical velocities. Also, we determine the mean of the Galaxy rotation curve for Galactocentric distances from 4 to 18 kpc by averaging Galactic azimuths in the range −30° < θ < + 30° about the direction Galactic Centre – Sun – Galactic anticentre. Maps of the velocity components and of their partial derivatives with respect to coordinates within 10 kpc of the Sun reveal complex substructures, which provide clear evidence of non-axisymmetric features of the Galaxy. Finally, we show evidence of differences in the Northern and Southern hemispheres stellar velocity fields.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".