Testing gravity on large scales by combining weak lensing with galaxy clustering using CFHTLenS and BOSS CMASS
Bibliographic record
Abstract
We measure a combination of gravitational lensing, galaxy clustering and redshift-space distortions (RSDs) called EG. The quantity EG probes both parts of metric potential and is insensitive to galaxy bias and σ8. These properties make it an attractive statistic to test lambda cold dark matter, general relativity and its alternate theories. We have combined CMASS Data Release 11 with CFHTLenS and recent measurements of β from RSD analysis, and find EG(z = 0.57) = 0.42 ± 0.056, a 13 per cent measurement in agreement with the prediction of general relativity EG(z = 0.57) = 0.396 ± 0.011 using the Planck 2015 cosmological parameters. We have corrected our measurement for various observational and theoretical systematics. Our measurement is consistent with the first measurement of EG using cosmic microwave background lensing in place of galaxy lensing at small scales, but shows 2.8σ tension when compared with their final results including large scales. This analysis with future surveys will provide improved statistical error and better control over systematics to test general relativity and its alternate theories.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".