The Cluster Mass Function from Early Sloan Digital Sky Survey Data: Cosmological Implications
Bibliographic record
Abstract
The mass function of clusters of galaxies is determined from 400 deg 2 of early commissioning imaging data of the Sloan Digital Sky Survey using ~300 clusters in the redshift range z = 0.1-0.2. Clusters are selected using two independent selection methods: a matched filter and a red-sequence color-magnitude technique. The two methods yield consistent results. The cluster mass function is compared with large-scale cosmological simulations. We find a best-fit cluster normalization relation of σ 8 Ω = 0.33 ± 0.03 (for 0.1 ≲ Ω m ≲ 0.4) or, equivalently, σ 8 = (0.16/Ω m ) 0.6 . The amplitude of this relation is significantly lower than the previous canonical value, implying that either Ω m is lower than previously expected (Ω m = 0.16 if σ 8 = 1) or σ 8 is lower than expected (σ 8 = 0.7 if Ω m = 0.3). The shape of the cluster mass function partially breaks this classic degeneracy. We find best-fit parameters of Ω m = 0.19 ± and σ 8 = 0.9 ± . High values of Ω m (≳0.4) and low σ 8 (≲0.6) are excluded at ≳2 σ.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".