The inner halo of M 87: a first direct view of the red-giant population
Bibliographic record
Abstract
An unusually deep (V,I) imaging dataset for the Virgo supergiant M 87 with the Hubble Space Telescope ACS successfully resolves its brightest red-giant stars, reaching MI(lim) = −2.5. After assessing the photometric completeness and biasses, we use this material to estimate the metallicity distribution for the inner halo of M 87, finding that the distribution is very broad and likely to peak near [m/H] ≃ −0.4 and perhaps higher. The shape of the MDF strongly resembles that of the inner halo for the nearby giant E galaxy NGC 5128. As a byproduct of our study, we also obtain a preliminary measurement of the distance to M 87 with the TRGB (red-giant branch tip) method; the result is (m − M)0 = 31.12±0.14 (d = 16.7±0.9 Mpc). Averaging this result with three other recent techniques give a weighted mean d(M87) = (16.4 ± 0.5) Mpc.
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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 | 0.001 |
| 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".