The Far-away Blues: Exploring the Furthest Extents of the Boötes I Ultra-faint Dwarf Galaxy
Bibliographic record
Abstract
Abstract Establishing the spatial extents and the nature of the outer stellar populations of dwarf galaxies is necessary for the determination of their total masses, current dynamical states, and past evolution. We here describe our investigation of the outer stellar content of the Boötes I ultra-faint dwarf galaxy, a satellite of the the Milky Way. We identify candidate member blue horizontal branch and blue straggler stars of Boötes I, both tracers of the underlying ancient stellar population, using a combination of multiband Pan-STARRS photometry and Gaia astrometry. We find a total of twenty-four candidate blue horizontal branch member stars with apparent magnitudes and proper motions consistent with membership of Boötes I, nine of which reside at projected distances beyond the nominal King profile tidal radius derived from earlier fits to photometry. We also identify four blue straggler stars of appropriate apparent magnitude to be at the distance of Boötes I, but all four are too faint to have high-quality astrometry from Gaia. The outer blue horizontal branch stars that we have identified confirm that the spatial distribution of the stellar population of Boötes I is quite extended. The morphology on the sky of these outer envelope candidate member stars is evocative of tidal interactions, a possibility that we explore further with simple dynamical models.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.000 |
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".