Ultradiffuse Galaxies (UDGs) with Hyper Suprime-Cam. I. Revised Catalog of Coma Cluster UDGs*
Bibliographic record
Abstract
Abstract This is the first in a series of papers on the properties of ultradiffuse galaxies (UDGs) in clusters of galaxies. We present an updated catalog of UDGs in the Coma Cluster using g- and r-band images obtained with Hyper Suprime-Cam (HSC) of the Subaru telescope. We develop a method to find UDGs even in the presence of contaminating objects, such as halos and background galaxies. This study expands upon our previous works that covered about half the area of the Coma Cluster. The HSC observations covered the whole Coma Cluster up to the virial radius and beyond (an area twice as large as the previous studies) and doubled the numbers of UDGs (r eff, r ≥ 1.5 kpc) and sub-UDGs (1.0 ≤ r eff, r < 1.5 kpc) to 774 and 729, respectively. The new UDGs show internal properties consistent with those of previous studies (e.g., a Sérsic index of approximately 1), and are distributed across the cluster, with a concentration around the cluster center. The whole cluster coverage clearly revealed an excess of their distribution toward the east to southwest direction along the cluster center, where Coma connects to other large-scale structure, and where a known substructure exists (the NGC 4839 subgroup). The alignment of the UDG distribution along the large-scale structure around Coma supports the interpretation that most of them lie at the distance of the Coma Cluster and the NGC 4839 subgroup.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".