GalWeight Application: A Publicly Available Catalog of Dynamical Parameters of 1800 Galaxy Clusters from SDSS-DR13, (GalWCat19)
Bibliographic record
Abstract
Abstract Utilizing the SDSS-DR13 spectroscopic data set, we create a new publicly available catalog of 1800 galaxy clusters (GalWeight cluster catalog, GalWCat19) and a corresponding catalog of 34,471 identified member galaxies. The clusters are identified from overdensities in redshift phase space. The GalWeight technique introduced by Abdullah et al. is then applied to identify cluster members. The completeness of the cluster catalog (GalWCat19) and the procedure followed to determine cluster mass are tested on the Bolshoi N-body simulations. The 1800 GalWCat19 clusters range in redshift between 0.01 and 0.2 and have masses in the range of (0.4–14) × 1014 h −1 M ⊙. The cluster catalog provides a large number of cluster parameters, including sky position, redshift, membership, velocity dispersion, and mass at overdensities Δ = 500, 200, 100, and 5.5. The 34,471 member galaxies are identified within the radius at which the density is 200 times the critical density of the universe. The galaxy catalog provides the coordinates of each galaxy and the ID of the cluster that the galaxy belongs to. The cluster velocity dispersion scales with mass as = + (0.349 ± 0.142) , with a scatter of δ logσ = 0.06 ± 0.04. The catalogs are publicly available at https://mohamed-elhashash-94.webself.net/galwcat/ .
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.041 |
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".