A synthesis of data from fundamental plane and surface brightness fluctuation surveys
Bibliographic record
Abstract
We perform a series of comparisons between distance-independent photometric and spectroscopic properties used in the surface brightness fluctuation (SBF) and fundamental plane (FP) methods of early-type galaxy distance estimation. The data are taken from two recent surveys: the SBF Survey of Galaxy Distances and the Streaming Motions of Abell Clusters (SMAC) FP survey. We derive a relation between colour and Mg2 index using nearly 200 galaxies and discuss implications for Galactic extinction estimates and early-type galaxy stellar populations. We find that the reddenings from Schlegel et al. for galaxies with appear to be overestimated by per cent, but we do not find significant evidence for large-scale dipole errors in the extinction map. In comparison with stellar population models having solar elemental abundance ratios, the galaxies in our sample are generally too blue at a given Mg2; we ascribe this to the well-known enhancement of the α-elements in luminous early-type galaxies. We confirm a tight relation between stellar velocity dispersion σ and the SBF ‘fluctuation count’ parameter N¯, which is a luminosity-weighted measure of the total number of stars in a galaxy. The correlation between N¯ and σ is even tighter than that between Mg2 and σ. Finally, we derive FP photometric parameters for 280 galaxies from the SBF survey data set. Comparisons with external sources allow us to estimate the errors on these parameters and derive the correction necessary to bring them on to the SMAC system. The data are used in a forthcoming paper, which compares the distances derived from the FP and SBF methods.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".