The diverse nature of optical emission lines in brightest cluster galaxies: IFU observations of the central kiloparsec
Bibliographic record
Abstract
We present integral field spectroscopy of the nebular line emission in a sample of nine brightest cluster galaxies (BCGs). The sample was chosen to probe both cooling flow and non-cooling flow clusters, as well as a range of cluster X-ray luminosities. The line emission morphology and velocity gradients suggest a great diversity in the properties of the line emitting gas. While some BCGs show evidence for filamentary or patchy emission (Abell 1060, Abell 1668 and MKW 3s), others have extended emission (Abell 1204, Abell 2199), while still others have centrally concentrated emission (Abell 2052). We examine diagnostic line ratios to determine the dominant ionization mechanisms in each galaxy. Most of the galaxies show regions with active galactic nucleus like spectra, however, for two BCGs, Abell 1060 and Abell 1204, the emission line diagnostics suggest regions which can be described by the emission from young stellar populations. The diversity of emission-line properties in our sample of BCGs suggests that the emission mechanism is not universal, with different ionization processes dominating different systems. Given this diversity, there is no evidence for a clear distinction of the emission-line properties between cooling flow and non-cooling flow BCGs. It is not always cooling flow BCGs which show emission (or young stellar populations), and non-cooling flow BCGs which do not.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".