Observational Constraints on Higher Order Clustering up to<i>z</i>≃ 1
Bibliographic record
Abstract
We present constraints on the validity of the hierarchical gravitational instability theory and the evolution of biasing based on measurements of higher order clustering statistics in the Deeprange Survey, a catalog of ~710,000 galaxies with I AB ≤ 24 derived from a Kitt Peak National Observatory (KPNO) 4 m CCD imaging survey of a contiguous 4° × 4° region. We compute the three- and four-point angular correlation functions using a direct estimation for the former and the counts-in-cells technique for both. The skewness, s 3 , decreases by a factor of ≃3-4 as galaxy magnitude increases over the range 17 ≤ I ≤ 22.5 (0.1 ≲ z ≲ 0.8). This decrease is consistent with a small increase of the bias with increasing redshift, but not by more than a factor of 2 for the highest redshifts probed. Our results are strongly inconsistent, at about the 3.5-4 σ level, with typical cosmic string models in which the initial perturbations follow a non-Gaussian distribution; such models generally predict an opposite trend in the degree of bias as a function of redshift. We also find that the scaling relation between the three- and four-point correlation functions remains approximately invariant over the above magnitude range. The simplest model that is consistent with these constraints is a universe in which an initially Gaussian perturbation spectrum evolves under the influence of gravity combined with a low level of bias between the matter and the galaxies that decreases slightly from z ~ 0.8 to the current epoch.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".