Evolution of hierarchical clustering in the CFHTLS-Wide since z ∼ 1★
Bibliographic record
Abstract
We present measurements of higher order clustering of galaxies in the latest release of the Canada–France–Hawaii Telescope Legacy Survey (CFHTLS)-Wide. We construct a series of volume-limited sample of galaxies containing more than one million galaxies over the redshift range 0.2 < z < 1 in the four independent fields of the CFHTLS-Wide. Using a counts-in-cells technique we measure the variance |${\bar{\xi }}_2$| and the hierarchical moments |$S_{n}= {{\bar{\xi }}_n / {\bar{\xi }}_2^{n-1}}$| (3 ≤ n ≤ 5) as a function of redshift and angular scale. We find that the measured field-to-field scatter in our estimators is in excellent agreement with analytical predictions. At small scales, corresponding to the highly non-linear regime, we find tentative evidence at the 1σ level that the hierarchical moments increase with redshift. At large scales, corresponding to the weakly non-linear regime, our measurements are marginally consistent with perturbation theory predictions for standard Λ cold dark matter cosmology using a simple linear bias. The predictions of perturbation theory tend to slightly overestimate our measurements, which may be a signature of non-linear bias.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".