Asymmetric metallicity patterns in the stellar velocity space with RAVE
Bibliographic record
Abstract
We explore the correlations between velocity and metallicity and the possible distinct chemical signatures of the velocity over-densities of the local Galactic neighbourhood. We use the large spectroscopic survey RAVE and the Geneva Copenhagen Survey. We compare the metallicity distribution of regions in the velocity plane ($v_R,v_\\phi$) with that of their symmetric counterparts ($-v_R,v_\\phi$). We expect similar metallicity distributions if there are no tracers of a sub-population (e.g., a dispersed cluster, accreted stars), if the disk of the Galaxy is axisymmetric, and if the orbital effects of the spiral arms and the bar are weak. We find that the metallicity-velocity space of the solar neighbourhood is highly patterned. A large fraction of the velocity plane shows differences in the metallicity distribution when comparing symmetric $v_R$ regions. The typical differences in the median metallicity are of $0.05$ dex with a statistical significance of at least $95\\%$, and with values up to $0.6$ dex. For low azimuthal velocity $v_\\phi$, stars moving outwards in the Galaxy have on average higher metallicity than those moving inwards. These include stars in the Hercules and Hyades moving groups and other velocity branch-like structures. For higher $v_\\phi$, the stars moving inwards have higher metallicity than those moving outwards. The most likely interpretation of the metallicity asymmetry is that it is due to the orbital effects of the bar and the radial metallicity gradient of the disk. We present a simulation that supports this idea. We have also discovered a positive gradient in $v_\\phi$ with respect to metallicity at high metallicities, apart from the two known positive and negative gradients for the thick and thin disks, 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 | 0.000 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".