Cosmology from large-scale structure
Bibliographic record
Abstract
We reanalyse the anisotropic galaxy clustering measurement from the Baryon Oscillation Spectroscopic Survey (BOSS), demonstrating that using the full shape information provides cosmological constraints that are comparable to other low-redshift probes. We find Ωm= 0.317+0.015−0.019,σ8= 0.710±0.049, andh = 0.704 ± 0.024 for flat ΛCDM cosmologies using uninformative priors on Ωch2, 100θMC, ln1010As, andns, and a prior on Ωbh2that is much wider than current constraints. We quantify the agreement between thePlanck2018 constraints from the cosmic microwave background and BOSS, finding the two data sets to be consistent within a flat ΛCDM cosmology using the Bayes factor as well as the prior-insensitive suspiciousness statistic. Combining two low-redshift probes, we jointly analyse the clustering of BOSS galaxies with weak lensing measurements from the Kilo-Degree Survey (KV450). The combination of BOSS and KV450 improves the measurement by up to 45%, constrainingσ8 = 0.702 ± 0.029 andS8= σ8Ωm/0.3 = 0.728 ± 0.026. Over the full 5D parameter space, the odds in favour of a single cosmology describing galaxy clustering, lensing, and the cosmic microwave background are 7 ± 2. The suspiciousness statistic signals a 2.1 ± 0.3σtension between the combined low-redshift probes and measurements from the cosmic microwave background.
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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 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".