Is the Milky Way still breathing? RAVE–Gaia streaming motions
Bibliographic record
Abstract
We use data from the Radial Velocity Experiment (RAVE) and the Tycho-Gaia astrometric solution (TGAS) catalogue to compute the velocity fields yielded by the radial (VR), azimuthal (Vϕ),and vertical (Vz) components of associated Galactocentric velocity. We search in particular for variation in all three velocity components with distance above and below the disc mid-plane, as well as how each component of Vz (line-of-sight and tangential velocity projections) modifies the obtained vertical structure. To study the dependence of velocity on proper motion and distance, we use two main samples: a RAVE sample including proper motions from the Tycho-2, PPMXL, and UCAC4 catalogues, and a RAVE–TGAS sample with inferred distances and proper motions from the TGAS and UCAC5 catalogues. In both samples, we identify asymmetries in VR and Vz. Below the plane, we find the largest radial gradient to be ∂VR/∂R = −7.01 ± 0.61 km s−1 kpc−1, in agreement with recent studies. Above the plane, we find a similar gradient with ∂VR/∂R = −9.42 ± 1.77 km s−1 kpc−1. By comparing our results with previous studies, we find that the structure in Vz is strongly dependent on the adopted proper motions. Using the Galaxia Milky Way model, we demonstrate that distance uncertainties can create artificial wave-like patterns. In contrast to previous suggestions of a breathing mode seen in RAVE data, our results support a combination of bending and breathing modes, likely generated by a combination of external or internal and external mechanisms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".