JWST NIRCam Photometry: A Study of Globular Clusters Surrounding Bright Elliptical Galaxy VV 191a at z = 0.0513
Bibliographic record
Abstract
Abstract James Webb Space Telescope NIRCam images have revealed 154 reliable globular cluster (GC) candidates around the z = 0.0513 elliptical galaxy VV 191a after subtracting 34 likely interlopers from background galaxies inside our search area. NIRCam broadband observations are made at 0.9–4.5 μm using the F090W, F150W, F356W, and F444W filters. Using point-spread-function-matched photometry, the data are analyzed to present color–magnitude diagrams and color distributions that suggest a relatively uniform population of GCs, except for small fractions of reddest (5%–8%) and bluest (2%–4%) outliers. GC models in the F090W versus (F090W–F150W) diagram fit the NIRCam data well and show that the majority of GCs detected have a mass of ∼106.5 M ⊙, with metallicities [Fe/H] spanning the typical range expected for GCs (−2.5 ≲ [Fe/H]≲ 0.5). However, the models predict ∼0.3–0.4 mag bluer (F356W–F444W) colors than the NIRCam data for a reasonable range of GC ages, metallicities, and reddening. Although our data do not quite reach the luminosity function turnover, the measured luminosity function is consistent with previous measurements, suggesting an estimated peak at m AB ∼ −9.4 ± 0.2 mag in the F090W filter.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".