Origin Of Red Sequence Barred Spiral Galaxies
Bibliographic record
Abstract
Spiral galaxies contain spiral arms that are sites of ongoing star formation, typically making these galaxies appear blue in color. Several studies, however, have recently found that a small fraction of cluster spiral galaxies (~10%) appear red in color. These studies have proposed several mechanisms to explain the red color of spiral galaxies, including bar instabilities. The research goal of this thesis is to contrast and compare imaging data for a sample of face-on red-sequence (RS) and non-red-sequence (NRS) barred spiral galaxies selected from 67 low-redshift galaxy clusters. These data were collected from observations obtained using the 3.6-meter Canada-France-Hawaii Telescope, the 0.9-meter telescope at the Kitt Peak National Observatory, and archival data from the WIde-field Nearby Galaxy-cluster Survey. The ELLIPSE and BMODEL tasks in the STSDAS package of the Image Reduction Analysis Facility software were used to model the central bulge of spiral galaxies, and the IMARITH task was used to subtract the model from the parent image. The ELLIPSE task outputs an STSDAS table file containing isophote fit values that are used to calculate bar length, bar width, and galaxy size. These values were used to calculate bar fractions of all galaxies in the sample. Comparison of bar fractions of the galaxies between the RS and NRS sample showed no statistically significant difference.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".