Surface Brightness Properties of LSB Galaxies with the International Liquid Mirror Telescope
Bibliographic record
Abstract
Low surface brightness (LSB) galaxies make up a significant fraction of the luminosity density of the local universe. Their low surface brightness suggests a different formation and evolution process compared to more-typical high-surface-brightness galaxies. This study presents an analysis of LSB galaxies found in images obtained by the International Liquid Mirror Telescope during the observation period from October 24 to November 1, 2022. 3,092 LSB galaxies were measured and separated into blue and red LSB categories based on their $g'-i'$ colours. In these samples, the median effective radius is 4.7 arcsec, and the median value of the mean surface brightness within the effective radius is 26.1 mag arcsec$^{-2}$. The blue LSB galaxies are slightly brighter than the red LSB galaxies. No significant difference of ellipticity was found between the blue and the red LSB galaxies.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".