Broadband photometric analysis of the stellar populations in brightest cluster galaxies of X-ray luminous galaxy clusters
Bibliographic record
Abstract
We have analyzed broadband Hubble photometry available to study the brightest \ncluster galaxies (BCGs) in X-ray luminous clusters of galaxies. 18 cool-core (CC) \nand non-cool-core (NCC) BCGs span a redshift interval of 0.15 < z < 0.55 and \nwere identified by the Canadian Cluster Comparison Project (CCCP). I used this \nsample to build an analysis pipeline that reduces photometric data from the Hubble \nSpace Telescope to probe the properties of the stellar populations in the BCGs. We \napply the observed colors to constrain the parameters in the simple stellar population \nsynthesis models to produce the best fitting SEDs of the BCGs. By applying variable \nfit-parameters, we can build radial metallicity and mass density profiles and trace \nthe star-formation histories in the BCG. The stellar mass estimates will allow us to \nbuild improved mass profiles of the clusters and probe the evolutionary history of \nthe BCGs and the host clusters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".