The integrated Sachs–Wolfe signal from BOSS superstructures
Bibliographic record
Abstract
Cosmic structures leave an imprint on the microwave background radiation through the integrated Sachs–Wolfe (ISW) effect. We construct a template map of the linear signal using the Sloan Digital Sky Survey-III Baryon Acoustic Oscillation Survey at redshift 0.43 < z < 0.65. We verify the imprint of this map on the Planck cosmic microwave background (CMB) temperature map at the 97 per cent confidence level and show consistency with the density–temperature cross-correlation measurement. Using this ISW reconstruction as a template, we investigate the presence of ISW sources and further examine the properties of the Granett–Neyrinck–Szapudi supervoid and supercluster catalogue. We characterize the three-dimensional density profiles of these structures for the first time and demonstrate that they are significant structures. Model fits demonstrate that the supervoids are elongated along the line of sight and we suggest that this special orientation may be picked out by the void-finding algorithm in photometric redshift space. We measure the mean temperature profiles in Planck maps from public void and cluster catalogues. In an attempt to maximize the stacked ISW signal, we construct a new catalogue of superstructures based upon local peaks and troughs of the gravitational potential. However, we do not find a significant correlation between these structures and the CMB temperature.
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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 | 0.002 |
| 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 | 0.000 | 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".