Deep imaging of the shell elliptical galaxy NGC 3923 with MegaCam
Bibliographic record
Abstract
Context. The elliptical galaxy NGC 3923 is known to be surrounded by a number of stellar shells, probable remnants of an accreted galaxy. Despite its uniqueness, the deepest images of its outskirts come from the 1980s. On the basis of the modified Newtonian dynamics (MOND), it has recently been predicted that a new shell lies in this region. Aims. We obtain the deepest image ever of the galaxy, map the tidal features in it, and search for the predicted shell. Methods. The image of the galaxy was taken by the MegaCam camera at the Canada-France-Hawaii Telescope in the g′-band. It reached the surface-brightness limit of 29 mag arcsec-2. In addition, we reanalyzed an archival HST image of the galaxy. Results. We detected up to 42 shells in NGC 3923. This is by far the highest number among all shell galaxies. We present the description of the shells and other tidal features in the galaxy. A probable progenitor of some of these features was discovered. The shell system likely originates from two or more progenitors. The predicted shell was not detected, but the new image revealed that the prediction was based on incorrect assumptions and poor data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".