Cosmological parameters derived from the final (PR4) Planck data release
Bibliographic record
Abstract
We present constraints on cosmological parameters using maps from the last Planck data release (PR4). In particular, we detail an upgraded version of the cosmic microwave background likelihood, HiLLiPoP, based on angular power spectra and relying on a physical modelling of the foreground residuals in the spectral domain. This new version of the likelihood retains a larger sky fraction (up to 75%) and uses an extended multipole range. Using this likelihood, along with low-l measurements from LoLLiPoP, we derive constraints on $Λ$CDM parameters that are in good agreement with previous Planck 2018 results, but with 10% to 20% smaller uncertainties. We demonstrate that the foregrounds can be accurately described in spectra domain with only negligible impact on $Λ$CDM parameters. We also derive constraints on single-parameter extensions to $Λ$CDM including $A_L$, $Ω_K$, $N_{eff}$, and $\sum m_ν$. Noteworthy results from this updated analysis include a lensing amplitude value of $A_L = 1.039 \pm 0.052$, which aligns more closely with theoretical expectations within the $Λ$CDM framework. Additionally, our curvature measurement, $Ω_K = -0.012 \pm 0.010$, now demonstrates complete consistency with a flat universe, and our measurement of $S_8$ is closer to the measurements derived from large-scale structure surveys (at the 1.6$σ$ level). We also add constraints from PR4 lensing, making the combination the most constraining data set that is currently available from Planck. Additionally we explore adding baryon acoustic oscillation data, which tightens limits on some particular extensions to the standard cosmology.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.013 |
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".