Metallicity and α-Element Abundance Gradients along the Sagittarius Stream as Seen by APOGEE
Bibliographic record
Abstract
Abstract Using 3D positions and kinematics of stars relative to the Sagittarius (Sgr) orbital plane and angular momentum, we identify 166 Sgr stream members observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) that also have Gaia DR2 astrometry. This sample of 63/103 stars in the Sgr trailing/leading arm is combined with an APOGEE sample of 710 members of the Sgr dwarf spheroidal core (385 of them newly presented here) to establish differences of 0.6 dex in median metallicity and 0.1 dex in [α/Fe] between our Sgr core and dynamically older stream samples. Mild chemical gradients are found internally along each arm, but these steepen when anchored by core stars. With a model of Sgr tidal disruption providing estimated dynamical ages (i.e., stripping times) for each stream star, we find a mean metallicity gradient of 0.12 ± 0.03 dex Gyr−1 for stars stripped from Sgr over time. For the first time, an [α/Fe] gradient is also measured within the stream, at 0.02 ± 0.01 dex Gyr−1 using magnesium abundances and at 0.04 ± 0.01 dex Gyr−1 using silicon, which imply that the Sgr progenitor had significant radial abundance gradients. We discuss the magnitude of those inferred gradients and their implication for the nature of the Sgr progenitor within the context of the current family of Milky Way satellite galaxies, and we suggest that more sophisticated Sgr models are needed to properly interpret the growing chemodynamical detail we have on the Sgr system.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".