Bibliographic record
Abstract
Abstract Stellar dynamical model globular clusters are introduced into reconstituted versions of the dark matter halos of the Via Lactea II (VL-2) simulation to follow the star cluster tidal mass-loss and stellar stream formation. The clusters initially evolve within their local sub-galactic halo, later being accreted into the main halo. Stars are continually removed from the clusters, but those that emerged in the sub-galactic halos are dispersed in a wide stream when accreted into the main halo. Thin tidal streams that survive to the present can begin to form once a cluster is in the main halo. A higher-redshift start places the star clusters in denser halos, where they are subject to stronger tides leading to higher average mass-loss rates. A z = 3 start leads to a rich set of star streams, with nearly all within 100 kpc having a remnant progenitor star cluster in the stream. In contrast, with a z = 8 start, all star clusters that are accreted onto the main halo are completely dissolved. These results are compared to the available data on Milky Way streams, where the majority of streams do not have clearly associated globular clusters, which, if generally true, suggests that there were at least twice as many massive globular clusters at high redshift.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".