The Morphological Content of 10 EDisCS Clusters at 0.5 <<i>z</i>< 0.8
Bibliographic record
Abstract
We describe Hubble Space Telescope (HST) imaging of 10 of the 20 ESO Distant Cluster Survey (EDisCS) fields. Each ~40 arcmin^2 field was imaged in the F814W filter with the Advanced Camera for Surveys Wide Field Camera. Based on these data, we present visual morphological classifications for the ~920 sources per field that are brighter than I_(auto) = 23 mag. We use these classifications to quantify the morphological content of 10 intermediate-redshift (0.5 < z < 0.8) galaxy clusters within the HST survey region. The EDisCS results, combined with previously published data from seven higher redshift clusters, show no statistically significant evidence for evolution in the mean fractions of elliptical, S0, and late-type (Sp+Irr) galaxies in clusters over the redshift range 0.5 < z < 1.2. In contrast, existing studies of lower redshift clusters have revealed a factor of ~2 increase in the typical S0 fraction between z = 0.4 and 0, accompanied by a commensurate decrease in the Sp+Irr fraction and no evolution in the elliptical fraction. The EDisCS clusters demonstrate that cluster morphological fractions plateau beyond z ≈ 0.4. They also exhibit a mild correlation between morphological content and cluster velocity dispersion, highlighting the importance of careful sample selection in evaluating evolution. We discuss these findings in the context of a recently proposed scenario in which the fractions of passive (E, S0) and star-forming (Sp, Irr) galaxies are determined primarily by the growth history of clusters. \n
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".