Constraining primordial magnetic fields through large scale structure
Bibliographic record
Abstract
We study primordial magnetic field effects on the matter perturbations in the universe. We assume magnetic field generation prior to the big bang nucleosynthesis (BBN), i.e., during the radiation-dominated epoch of the universe expansion, but do not limit analysis by considering a particular magnetogenesis scenario. Contrary to previous studies, we limit the total magnetic field energy density and not the smoothed amplitude of the magnetic field at large (of the order of 1 Mpc) scales. We review several cosmological signatures, such as halo abundance, thermal Sunyaev-Zel'dovich (tSZ) effect, and Lyman-α data. For a cross-check we compare our limits with that obtained through the CMB faraday rotation effect and BBN. The limits range between 1.5 nG and 4.5 nG for n[subscript B]∈ in (– 3; –1.5).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".