Near-infrared surface brightness fluctuation measurements with the <i>Hubble Space Telescope</i>'s WFC3/IR channel
Bibliographic record
Abstract
Abstract The surface brightness fluctuation (SBF) method at near-infrared (NIR) wavelengths is a powerful tool for estimating distances to unresolved stellar systems with high precision. The IR channel of the Wide Field Camera 3 (WFC3), installed on board the Hubble Space Telescope (HST) in 2009, has a greater sensitivity and a wider field of view than the previous generation of HST IR instruments, making it much more efficient for measuring distances to early-type galaxies in the Local Volume. To take full advantage of its capabilities, we need to empirically calibrate the SBF distance method for WFC3's NIR passbands. We present the SBF measurements for the WFC3/IR F160W bandpass filter using observations of 16 early-type galaxies in the Fornax and Virgo Clusters. These have been combined with existing (g475–z850) color measurements from the Advanced Camera for Surveys Virgo and Fornax Cluster Surveys to derive a space-based H160-band SBF relation as a function of color. We have also compared the absolute SBF magnitudes to those predicted by evolutionary population synthesis models in order to study stellar population properties in the target galaxies.
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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 | 0.001 | 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 | 0.000 | 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".