THE CARNEGIE-IRVINE GALAXY SURVEY. II. ISOPHOTAL ANALYSIS
Bibliographic record
Abstract
The Carnegie-Irvine Galaxy Survey (CGS) is a comprehensive investigation of the physical properties of a complete, representative sample of 605 bright ( B T ⩽ 12.9 mag) galaxies in the southern hemisphere. This contribution describes the isophotal analysis of the broadband ( BVRI ) optical imaging component of the project. We pay close attention to sky subtraction, which is particularly challenging for some of the large galaxies in our sample. Extensive crosschecks with internal and external data confirm that our calibration and sky subtraction techniques are robust with respect to the quoted measurement uncertainties. We present a uniform catalog of one-dimensional radial profiles of surface brightness and geometric parameters, as well as integrated colors and color gradients. Composite profiles highlight the tremendous diversity of brightness distributions found in disk galaxies and their dependence on Hubble type. A significant fraction of S0 and spiral galaxies exhibit non-exponential profiles in their outer regions. We perform Fourier decomposition of the isophotes to quantify non-axisymmetric deviations in the light distribution. We use the geometric parameters, in conjunction with the amplitude and phase of the m = 2 Fourier mode, to identify bars and quantify their size and strength. Spiral arm strengths are characterized using the m = 2 Fourier profiles and structure maps. Finally, we utilize the information encoded in the m = 1 Fourier profiles to measure disk lopsidedness. The databases assembled here and in Paper I lay the foundation for forthcoming scientific applications of CGS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.020 |
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".