Bibliographic record
Abstract
Pal 5 is a low-mass, low-velocity-dispersion, globular cluster with spectacular tidal tails. We use the Sloan Digital Sky Survey Data Release 8 data to extend the density measurements of the trailing star stream to 23 deg distance from the cluster, at which point the stream runs off the edge of the available sky coverage. The size and the number of gaps in the stream are measured using a filter which approximates the structure of the gaps found in stream simulations. We find 5 gaps that are at least 99% confidence detections with about a dozen gaps at 90% confidence. The statistical significance of a gap is estimated using bootstrap resampling of the control regions on either side of the stream. The density minimum closest to the cluster is likely the result of the epicyclic orbits of the tidal outflow and has been discounted. To create the number of 99% confidence gaps per unit length at the mean age of the stream requires a halo population of nearly a thousand dark matter sub-halos with peak circular velocities above 1 km s −1 within 30 kpc of the galactic center. These numbers are a factor of about three below cold stream simulation at this sub-halo mass or velocity but, given the uncertainties in both measurement and more realistic warm stream modeling, are in substantial agreement with the LCDM prediction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".