Bibliographic record
Abstract
By modelling the axis ratio distribution of Sloan Digital Sky Survey (SDSS) Data Release 8 galaxies, we find the intrinsic 3D shapes of spirals and ellipticals. We use morphological information from the Galaxy Zoo project and assume a non-parametric distribution intrinsic of shapes, while taking into account dust extinction. We measure the dust extinction of the full sample of spiral galaxies and find a smaller value than previous estimations, with an edge-on extinction of |$E_0 = 0.284^{+0.015}_{-0.026}$| in the SDSS r band. We also find that the distribution of minor to major axis ratio has a mean value of 0.267 ± 0.009, slightly larger than previous estimates mainly due to the lower extinction used; the same affects the circularity of galactic discs, which are found to be less round in shape than in previous studies, with a mean ellipticity of 0.215 ± 0.013. For elliptical galaxies, we find that the minor to major axis ratio, with a mean value of 0.584 ± 0.006, is larger than previous estimations due to the removal of spiral interlopers present in samples with morphological information from photometric profiles. These interlopers are removed when selecting ellipticals using Galaxy Zoo data. We find that the intrinsic shapes of galaxies and their dust extinction vary with absolute magnitude, colour and physical size. We find that bright elliptical galaxies are more spherical than faint ones, a trend that is also present with galaxy size, and that there is no dependence of elliptical galaxy shape with colour. For spiral galaxies, we find that the reddest ones have higher dust extinction as expected, due to the fact that this reddening is mainly due to dust. We also find that the thickness of discs increases with luminosity and size, and that brighter, smaller and redder galaxies have less round discs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".