The ATLAS3D project – XVII. Linking photometric and kinematic signatures of stellar discs in early-type galaxies
Bibliographic record
Abstract
We analyse the morphological structures in galaxies of the ATLAS 3D sample by fitting a single Sérsic profile and decomposing all non-barred objects (180 of 260 objects) in two components parametrized by an exponential and a general Sérsic function.The aim of this analysis is to look for signatures of discs in light distributions of nearby early-type galaxies and compare them to kinematic properties.Using Sérsic index from single-component fits for a distinction between slow and fast rotators, or even late-and early-type galaxies, is not recommended.Assuming that objects with n > 3 are slow rotators (or ellipticals), there is only a 22 per cent probability to correctly classify objects as slow rotators (or 37 per cent of previously classified as ellipticals).We show that exponential sub-components, as well as light profiles fitted with only a single component of a low Sérsic index, can be linked with the kinematic evidence for discs in early-type galaxies.The median disc-to-total light ratio for fast and slow rotators is 0.41 and 0.0, respectively.Similarly, the median Sérsic indices of the bulge (general Sérsic component) are 1.7 and 4.8 for fast and slow rotators, respectively.Overall, discs or disc-like structures are present in 83 per cent of early-type galaxies which do not have bars, and they show a full range of disc-to-total light ratios.Discs in early-type galaxies contribute with about 40 per cent to the total mass of the analysed (non-barred) objects.The decomposition into
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.040 |
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".