Small scale contributions to the cosmic microwave background: a coherent analysis
Bibliographic record
Abstract
We re-analyse Cosmic Microwave Background data from experiments probing both large and small scales. We assume that measured anisotropies are due not only to primary fluctuations but also, especially at small scales, to secondary effects (namely the Sunyaev-Zel'dovich effect) and possible point source contamination. We first consider primary and secondary anisotropies. For the first time in such analyses, the cosmological dependence of secondary fluctuations is fully taken into account. We show that in that case a higher value of the normalisation is preferred, as found by previous studies, but also higher values of the optical depth τ and power spectrum index ns are needed. In the second part, we include possible contaminations from unresolved and unremoved point sources. We discuss the effects on the cosmological parameters. We further obtain the best combination of relative contributions of the three kinds of sources to the measured microwave power on small scales at each frequency. Our method allows us to simultaneously obtain cosmological parameters and explain the so-called small scale power excess in a consistent way.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".