Bibliographic record
Abstract
Abstract High spatial-resolution measurements of surface brightness fluctuations (SBFs) with the Hubble Space Telescope (HST) provide the most precise distances available to early-type galaxies beyond the Local Group. The observable SBF magnitude in a given bandpass is a basic property of any stellar system, corresponding to a ratio of the first and second moments of the stellar luminosity function. Calibration of the method has presented challenges, but we now have an excellent empirical determination of how the SBF observable varies with galaxy color in broad bandpasses at the red end of the optical spectrum, and we are working towards a similar calibration for HST's Wide-Field Camera 3 in the near-infrared wavelength range, where the SBF magnitudes are considerably brighter. From HST Advanced Camera for Surveys data, we have determined the relative distances of the Virgo and Fornax clusters to within a precision of 2%, and resolved their internal structures. More recent measurements allow us to tie the Coma cluster, the standard of comparison for distant cluster studies, to the same precise distance scale. The SBF method can be calibrated in an absolute sense either empirically using Cepheids or theoretically based on stellar population models. The agreement between model and empirical zero points provides an independent confirmation of the Cepheid distance scale.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".