An extensive catalogue of early-type galaxies in the nearby Universe
Bibliographic record
Abstract
We present a catalogue of 1715 early-type galaxies from the literature, spanning the luminosity range from faint dwarf spheroidal galaxies to giant elliptical galaxies. The aim of this catalogue is to be one of the most comprehensive and publicly available collections of data on early-type galaxies. The emphasis in this catalogue lies on dwarf elliptical galaxies, for which some samples with detailed data have been published recently. For almost all of the early-type galaxies included in it, this catalogue contains data on their locations, distances, redshifts, half-light radii, the masses of their stellar populations and apparent magnitudes in various passbands. Data on metallicity and various colours are available for a majority of the galaxies presented here. The data on magnitudes, colours, metallicities and masses of the stellar populations are supplemented with entries that are based on fits to data from simple stellar population models and existing data from observations. Also, some simple transformations have been applied to the data on magnitudes, colours and metallicities in this catalogue, in order to increase the homogeneity of these data. Estimates on the Sérsic profiles, internal velocity dispersions, maximum rotational velocities, dynamical masses and ages are listed for several hundreds of the galaxies in this catalogue. Finally, each quantity listed in this catalogue is accompanied with information on its source, so that users of this catalogue can easily exclude data that they do not consider as reliable enough for their purposes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.059 |
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".