A slow spin to win: The gradual kinematic evolution across metallicities of the proto-Galaxy to the high- <i>α</i> disc
Bibliographic record
Abstract
Context . Observational studies are identifying stars thought to be remnants from the earliest stages of the Milky Way’s hierarchical mass assembly, referred to as the proto-Galaxy. Aims . We used red giant stars with kinematics from Gaia DR3 RVS data and [ α /M] and [M/H] estimates from low-resolution Gaia XP spectra to investigate the relationship between azimuthal velocity and metallicity. Our aim is to understand the transition from a chaotic proto-Galaxy to a well-ordered rotating (high- α ) disc-like population. Methods . To analyze the structure of the data in [M/H]−v ϕ space for both high- and low- α samples with carefully defined α -separation, we developed a model with two Gaussian components in v ϕ , one representing a disc-like population and the other a halo-like population. This model is designed to capture the conditional distribution P(v ϕ |[M/H]) with a two-component Gaussian mixture model with fixed means and standard deviations in the azimuthal velocities. To quantify the spin-up of the high- α disc population, we extended this two-component model by allowing the mean velocity and velocity dispersion to vary between the spline knots across the metallicity range used. We also compared our findings with existing literature using traditional Gaussian mixture modelling in bins of [M/H] and investigated using orbital circularity instead of azimuthal velocity. Results . Our findings show that the metal-poor high- α disc gradually spins up across [M/H] ∼−1.7 to −1, while the low- α sample exhibits a sharp transition at [M/H] ≍−1. This latter result is due to the accreted (mostly Gaia -Enceladus-Sausage) debris dominating the metal-poor end, underscoring the critical role of [ α /M] selection in studying the Milky Way’s (old, high- α ) disc evolution. Conclusions . These results indicate that the proto-Galaxy underwent a slow, monotonic spin-up phase over increasing metallicities rather than a rapid, dramatic spin-up at [M/H] ∼−1, as previously inferred in the literature.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".