No globular cluster progenitors in Milky Way satellite galaxies
Bibliographic record
Abstract
ABSTRACT In order to find the possible progenitors of Milky Way (MW) globular clusters, we perform orbit integrations to track the orbits of 170 Galactic globular clusters and the 11 classical MW satellite galaxies backwards in time for 11 Gyr in an MW-plus-satellites potential including the response of the MW to the infall of the Large Magellanic Cloud and the effect of dynamical friction on the satellites. To evaluate possible past associations, we devise a globular-cluster–satellite binding criterion based on the satellite’s tidal radius and escape velocity and we test it on globular clusters associated with the Sagittarius dwarf and on dwarf galaxies associated with the Large Magellanic Cloud. For these, we successfully recover the dynamical associations highlighted by previous studies and we derive their time of accretion by the Galaxy by using Gaia EDR3 data. Assuming that MW globular clusters are and have been free of dark matter and thus consist of stars alone, we demonstrate that none of the globular clusters show any clear association with the eight classical dwarf spheroidal galaxies even though a large fraction of them are believed to be accreted. This means that accreted globular clusters either came in as part of now-disrupted satellite galaxies or that globular clusters may have had dark matter haloes in the past – as suggested by the similar metallicity between globular clusters and dwarf galaxies.
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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 | 0.001 |
| 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".