Mass‐to‐Light Ratios of Galaxy Groups from Weak Lensing
Bibliographic record
Abstract
We present the findings of our weak-lensing study of a sample of 116 CNOC2 galaxy groups. The lensing signal is used to estimate the mass-to-light ratio of these galaxy groups. The best-fit isothermal sphere model to our lensing data has an Einstein radius of 0 88 ± 0 12, which corresponds to a shear-weighted velocity dispersion of 245 ± 18 km s -1 . The mean mass-to-light ratio within 1 h -1 Mpc is 185 ± 28 h M ☉ L and is independent of radius from the group center. The signal-to-noise ratio of the shear measurement is sufficient to split the sample into subsets of "poor" and "rich" galaxy groups. The poor galaxy groups were found to have an average velocity dispersion of 193 ± 38 km s -1 and a mass-to-light ratio of 134 ± 26 h M ☉ L , while the rich galaxy groups have a velocity dispersion of 270 ± 39 km s -1 and a mass-to-light ratio of 278 ± 42 h M ☉ L , similar to the mass-to-light ratio of clusters. This steep increase in the mass-to-light ratio as a function of mass suggests that the mass scale of ~10 13 M ☉ is where the transition between the actively star-forming field environment and the passively evolving cluster environment occurs. This is the first such detection from weak lensing.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".