QUANTIFYING DISCORDANCE IN THE 2015 PLANCK CMB SPECTRUM
Bibliographic record
Abstract
ABSTRACT We examine the internal consistency of the Planck 2015 cosmic microwave background (CMB) temperature anisotropy power spectrum. We show that tension exists between cosmological constant cold dark matter ( ) model parameters inferred from multipoles (roughly those accessible to Wilkinson Microwave Anisotropy Probe), and from , particularly the CDM density, , which is discrepant at for a Planck -motivated prior on the optical depth, . We find some parameter tensions to be larger than previously reported because of inaccuracy in the code used by the Planck Collaboration to generate model spectra. The Planck constraints are also in tension with low-redshift data sets, including Planck ’s own measurement of the CMB lensing power spectrum ( ), and the most precise baryon acoustic oscillation scale determination ( ). The Hubble constant predicted by Planck from , km s Mpc−1, disagrees with the most precise local distance ladder measurement of km s Mpc−1 at the level, while the Planck value from , km s Mpc−1, is consistent within . A discrepancy between the Planck and South Pole Telescope high-multipole CMB spectra disfavors interpreting these tensions as evidence for new physics. We conclude that the parameters from the Planck high-multipole spectrum probably differ from the underlying values due to either an unlikely statistical fluctuation or unaccounted-for systematics persisting in the Planck data.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".