Joint Cosmic Microwave Background and Weak Lensing Analysis: Constraints on Cosmological Parameters
Bibliographic record
Abstract
We use cosmic microwave background (CMB) observations together with the red-sequence cluster survey weak lensing results to derive constraints on a range of cosmological parameters. This particular choice of observations is motivated by their robust physical interpretation and complementarity. Our combined analysis, including a weak nucleosynthesis constraint, yields accurate determinations of a number of parameters including the amplitude of fluctuations ${\ensuremath{\sigma}}_{8}=0.89\ifmmode\pm\else\textpm\fi{}0.05$ and matter density ${\ensuremath{\Omega}}_{m}=0.30\ifmmode\pm\else\textpm\fi{}0.03$. We also find a value for the Hubble parameter of ${H}_{0}=70\ifmmode\pm\else\textpm\fi{}3\text{ }\mathrm{k}\mathrm{m}\text{ }{\mathrm{s}}^{\ensuremath{-}1}\text{ }{\mathrm{M}\mathrm{p}\mathrm{c}}^{\ensuremath{-}1}$, in good agreement with the Hubble Space Telescope key-project result. We conclude that the combination of CMB and weak lensing data provides some of the most powerful constraints available in cosmology today.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".