Testing formation mechanisms of the Milky Way's thick disc with RAVE
Bibliographic record
Abstract
We study the eccentricity distribution of a thick-disc sample of stars (defined as those with Vy > 50 km s−1 and 1 < |z|/kpc < 3) observed in the Radial Velocity Experiment (RAVE). We compare this distribution with those obtained in four simulations of galaxy formation taken from the literature as compiled by Sales et al. Each simulation emphasizes different scenarios for the origin of such stars (satellite accretion, heating of a pre-existing thin disc during a merger, radial migration, and gas-rich mergers). We find that the observed distribution peaks at low eccentricities and falls off smoothly and rather steeply to high eccentricities. This finding is fairly robust to changes in distances and to plausible assumptions about thin-disc contamination. Our results favour models where the majority of stars formed in the Galaxy itself on orbits of modest eccentricity and disfavour the pure satellite accretion case. A gas-rich merger origin where most of the stars form ‘in situ’ appears to be the most consistent with our data.
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".