The orbital anisotropy profiles of nearby globular clusters from Gaia Data Release 2
Bibliographic record
Abstract
Gaia Data Release 2 provides a wealth of data to study the internal structure of nearby globular clusters (GCs). We use this data to investigate the internal kinematics of 10 nearby GCs, with a particular focus on their poorly studied outer regions. We apply a strict set of selection criteria to remove contaminating sources and create pure cluster-member samples over a significant fraction of the radial range of each cluster. We confirm previous measurements of rotation (or a lack thereof) in the inner regions of several clusters, while extending the detection of rotation well beyond where it was previously measured and finding a steady decrease in rotation with radius. We also determine the orbital anisotropy profile and determine that clusters have isotropic cores, are radially anisotropic out to ≈4 half-light radii or |$35{{\ \rm per\ cent}}$| of their limiting radii, and are then isotropic out to the limits of our data sets. We detect for the first time the presence of radial anisotropy in M 22, while confirming previous detections of radial anisotropy in 47 Tuc, M 13, M 15, and ω Cen’s innermost regions. The implications of these measurements are that clusters can be separated into two categories: (1) clusters with observed radial anisotropy that likely formed tidally underfilling or are dynamically young, and (2) clusters that are primarily isotropic that likely formed tidally filling or are dynamically old.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| 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 | 0.002 |
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".