Census and classification of low-surface-brightness structures in nearby early-type galaxies from the MATLAS survey
Bibliographic record
Abstract
ABSTRACT The morphology of galaxies gives essential constraints on the models of galaxy evolution. The morphology of the features in the low-surface-brightness (LSB) regions of galaxies has not been fully explored yet because of observational difficulties. Here we present the results of our visual inspections of very deep images of a large volume-limited sample of 177 nearby massive early-type galaxies from the MATLAS survey. The images reach a surface-brightness limit of 28.5–29 mag arcsec−2 in the g′ band. Using a dedicated navigation tool and questionnaire, we looked for structures at the outskirts of the galaxies such as tidal shells, streams, tails, disturbed outer isophotes, or peripheral star-forming discs, and simultaneously noted the presence of contaminating sources, such as Galactic cirrus. We also inspected internal substructures such as bars and dust lanes. We discuss the reliability of this visual classification investigating the variety of answers made by the participants. We present the incidence of these structures and the trends of the incidence with the mass of the host galaxy and the density of its environment. We find an incidence of shells, stream, and tails of approximately 15 per cent, about the same for each category. For galaxies with masses over 1011 M⊙, the incidence of shells and streams increases about 1.7 times. We also note a strong unexpected anticorrelation of the incidence of Galactic cirrus with the environment density of the target galaxy. Correlations with other properties of the galaxies, and comparisons to model predictions, will be presented in future papers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".