Uncovering fossils of the distant Milky Way with UNIONS: NGC 5466 and its stellar stream
Bibliographic record
Abstract
ABSTRACT We examine the spatial clustering of blue horizontal branch (BHB) stars from the u-band of the Canada–France Imaging Survey (CFIS, a component of the Ultraviolet Near-Infrared Optical Northern Survey, or UNIONS). All major groupings of stars are associated with previously known satellites, and among these is NGC 5466, a distant (16 kpc) globular cluster. NGC 5466 reportedly possesses a long stellar stream, although no individual members of the stream have previously been identified. Using both BHBs and more numerous red giant branch stars cross-matched to Gaia Data Release 2, we identify extended tidal tails from NGC 5466 that are both spatially and kinematically coherent. Interestingly, we find that this stream does not follow the same path as the previous detection at large distances from the cluster. We trace the stream across 31° of sky and show that it exhibits a very strong distance gradient in the range 10 < Rhelio < 30 kpc. We compare our observations to simple dynamical models of the stream and find that they are able to broadly reproduce the overall path and kinematics. The fact that NGC 5466 is so distant, traces a wide range of Galactic distances, has an identified progenitor, and appears to have recently had an interaction with the Galaxy’s disc makes it a unique test-case for dynamical modelling of the Milky Way.
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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 | 0.000 | 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".