Tidal Debris Candidates from the $ω$ Centauri Accretion Event and its Role in Building Up the Milky Way Halo
Bibliographic record
Abstract
We identify stellar tidal debris from the $ω$ Centauri ($ω$ Cen) system among field stars in the APOGEE survey via chemical tagging using a neural network trained on APOGEE observations of the $ω$ Cen core. We find a total of 463 $ω$ Cen debris candidates have a probability $P > 0.8$ of sharing common patterns in their chemical abundances across a range of individual elements or element combinations, including [C+N], O, Mg, Al, Si, Ca, Ni, and Fe. Some debris candidates show prograde or retrograde disk-like kinematics, but most show kinematics consistent with the accreted halo, showing high radial actions, $J_{R}$, values. We find that a sample of Gaia-Sausage-Enceladus (GES) members are chemically distinct from the $ω$ Cen core, suggesting that $ω$ Cen is associated to an independent merger event shaping the Milky Way halo. However, a connection between GSE and $ω$ Cen cannot be ruled out. A detailed comparison with $N$-body simulations indicates that the $ω$ Cen progenitor was a massive dwarf galaxy ($\gtrsim 10^8 M_{\odot}$). The existence of a metal-poor high-$α$ chemically homogeneous halo debris is also reported.
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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 | 0.000 |
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".