THE SHAPE AND PROFILE OF THE MILKY WAY HALO AS SEEN BY THE CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY
Bibliographic record
Abstract
We use Canada–France–Hawaii Telescope Legacy Survey data for 170 deg 2 , recalibrated and transformed to the Sloan Digital Sky Survey ugri photometric system, to study the distribution of near-turnoff main-sequence stars in the Galactic halo along four lines of sight to heliocentric distances of ∼35 kpc. We find that the halo stellar number density profile becomes steeper at Galactocentric distances greater than R gal ∼ 28 kpc, with the power-law index changing from n inner = −2.62 ± 0.04 to n outer = −3.8 ± 0.1. In particular, we test a series of single power-law models and find them to be strongly disfavored by the data. The parameters for the best-fit Einasto profile are n = 2.2 ± 0.2 and R e = 22.2 ± 0.4 kpc. We measure the oblateness of the halo to be q ≡ c / a = 0.70 ± 0.01 and detect no evidence of it changing across the range of probed distances. The Sagittarius stream is detected in the l = 173° and b = −62° direction as an overdensity of [Fe/H] ∼ -1.5 dex stars at R gal ∼ 32 kpc, providing a new constraint for the Sagittarius stream and dark matter halo models. We also detect the Monoceros stream as an overdensity of [Fe/H] > -1.5 dex stars in the l = 232° and b = 26° direction at R gal ≲ 25 kpc. In the two sight lines where we do not detect significant substructure, the median metallicity is found to be independent of distance within systematic uncertainties ([Fe/H] ∼ -1.5 ± 0.1 dex).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".