Bibliographic record
Abstract
ABSTRACT Stellar streams are the inevitable end product of star cluster evolution, with the properties of a given stream being related to its progenitor. We consider how the dynamical history of a progenitor cluster, as traced by the evolution of its stellar mass function, is reflected in the resultant stream. We generate model streams by evolving star clusters with a range of initial half-mass relaxation times and dissolution times via direct N-body simulations. Stellar streams that dissolve quickly show no variation in the stellar mass function along the stream. Variation is, however, observed along streams with progenitor clusters that dissolve after several relaxation times. The mass function at the edges of a stream is approximately primordial, as it is populated by the first stars to escape the cluster before segregation occurs. Moving inwards the mass function steepens as the intermediate parts of the stream consist of mostly low-mass stars that escaped the cluster after some segregation has occurred. The centre of the stream is then marked by a flatter mass function, as the region is dominated by high-mass stars that quickly segregated to the progenitor cluster’s centre and were the last stars to become unbound. We further find that the maximum slope of the mass function along the stream and the rate at which it decreases with distance from the dissolved progenitor serve as proxies for the dynamical state reached by the progenitor cluster before dissolution; this may be able to be applied to observed streams with near-future observations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".