First‐Year <i>Wilkinson Microwave Anisotropy Probe</i> ( <i>WMAP</i> ) Observations: Determination of Cosmological Parameters
Bibliographic record
Abstract
WMAP precision data enables accurate testing of cosmological models. We find that the emerging standard model of cosmology, a flat Lambda-dominated universe seeded by nearly scale-invariant adiabatic Gaussian fluctuations, fits the WMAP data. With parameters fixed only by WMAP data, we can fit finer scale CMB measurements and measurements of large scle structure (galaxy surveys and the Lyman alpha forest). This simple model is also consistent with a host of other astronomical measurements. We then fit the model parameters to a combination of WMAP data with other finer scale CMB experiments (ACBAR and CBI), 2dFGRS measurements and Lyman alpha forest data to find the model's best fit cosmological parameters: h=0.71+0.04-0.03, Omega_b h^2=0.0224+-0.0009, Omega_m h^2=0.135+0.008-0.009, tau=0.17+-0.06, n_s(0.05/Mpc)=0.93+-0.03, and sigma_8=0.84+-0.04. WMAP's best determination of tau=0.17+-0.04 arises directly from the TE data and not from this model fit, but they are consistent. These parameters imply that the age of the universe is 13.7+-0.2 Gyr. The data favors but does not require a slowly varying spectral index. By combining WMAP data with other astronomical data sets, we constrain the geometry of the universe, Omega_tot = 1.02 +- 0.02, the equation of state of the dark energy w < -0.78 (95% confidence limit assuming w >= -1), and the energy density in stable neutrinos, Omega_nu h^2 < 0.0076 (95% confidence limit). For 3 degenerate neutrino species, this limit implies that their mass is less than 0.23 eV (95% confidence limit). The WMAP detection of early reionization rules out warm dark matter.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".