FAINT TIDAL FEATURES IN GALAXIES WITHIN THE CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY WIDE FIELDS
Bibliographic record
Abstract
We present an analysis of the detectability of faint tidal features in galaxies from the wide-field component of the Canada–France–Hawaii Telescope Legacy Survey. Our sample consists of 1781 luminous ( mag) galaxies in the magnitude range 15.5 mag < r ' < 17 mag and in the redshift range 0.04 < z < 0.2. Although we have classified tidal features according to their morphology (e.g., streams, shells, and tails), we do not attempt to interpret them in terms of their physical origin (e.g., major versus minor merger debris). Instead, we provide a catalog that is intended to provide raw material for future investigations which will probe the nature of low surface brightness substructure around galaxies. We find that around 12% of the galaxies in our sample show clear tidal features at the highest confidence level. This fraction rises to about 18% if we include systems with convincing, albeit weaker tidal features, and to 26% if we include systems with more marginal features that may or may not be tidal in origin. These proportions are a strong function of rest-frame color and of stellar mass. Linear features, shells, and fans are much more likely to occur in massive galaxies with stellar masses >10 10.5 M ☉ , and red galaxies are twice as likely to show tidal features than are blue 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".