The stellar mass of the <i>Gaia</i>-Sausage/Enceladus accretion remnant
Bibliographic record
Abstract
ABSTRACT The Gaia-Sausage/Enceladus (GS/E) structure is an accretion remnant that comprises a large fraction of the Milky Way’s stellar halo. We study GS/E using high-purity samples of kinematically selected stars from APOGEE DR16 and Gaia. Employing a novel framework to account for kinematic selection biases using distribution functions, we fit density profiles to these GS/E samples and measure their masses. We find that GS/E has a shallow density profile in the inner Galaxy, with a break between 15 and 25 kpc beyond which the profile steepens. We also find that GS/E is triaxial, with axis ratios 1:0.55:0.45 (nearly prolate), and the major axis is oriented about 80° from the Sun–Galactic centre line and 16° above the plane. We measure a stellar mass for GS/E of $1.45\, ^{+0.92}_{-0.51}\, \mathrm{(stat.)}\, ^{+0.13}_{-0.37} \mathrm{(sys.)}\ \times 10^{8}$ M⊙. Our mass estimate is lower than others in the literature, a finding we attribute to the excellent purity of the samples we work with. We also fit a density profile to the entire Milky Way stellar halo, finding a mass in the range of 6.7–8.4 × 108 M⊙, and implying that GS/E could make up as little as 15–25 per cent of the mass of the Milky Way stellar halo. Our lower stellar mass combined with standard stellar mass-to-halo mass relations implies that GS/E constituted a minor 1:8 mass-ratio merger at the time of its accretion.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.001 |
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".