Astrophysically motivated bulge-disc decompositions of Sloan Digital Sky Survey galaxies
Bibliographic record
Abstract
We present a set of bulge–disc decompositions for a sample of 71 825 Sloan Digital Sky Survey (SDSS) main-sample galaxies in the redshift range 0.003 < z < 0.05. We have fitted each galaxy with either a de Vaucouleurs (‘classical’) or an exponential (‘pseudo-’) bulge and an exponential disc. Two-dimensional Sérsic fits are performed when the two-component fits are not statistically significant or when the fits are poor, even in the presence of high signal-to-noise ratio (S/N). We study the robustness of our two-component fits by studying a bright subsample of galaxies and we study the systematics of these fits with decreasing resolution and S/N. Only 30 per cent of our sample have been fitted with two-component fits in which both components are non-zero. The g−r and g−i colours of each component for the two-component models are determined using linear templates derived from the r-band model. We attempt a physical classification of types of fits into disc galaxies, pseudo-bulges, classical bulges and ellipticals. Our classification of galaxies agrees well with previous large bulge plus disc (B+D) decomposed samples. Using our galaxy classifications, we find that Petrosian concentration is a good indicator of bulge-to-total ratio, while overall Sérsic index is not. Additionally, we find that the majority of green valley galaxies are bulge+disc galaxies. Furthermore, in the transition from green to red B+D galaxies, the total galaxy colour is most strongly correlated with the disc colour.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".