Why this work is in the frame
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Bibliographic record
Abstract
We report a measurement of cosmic shear correlations using an effective area of 6.5 sq. deg. of the VIRMOS deep imaging survey in progress at the Canada-France-Hawaii Telescope. We measured various shear correlation functions, the aperture mass statistic and the top-hat smoothed variance of the shear with a detection significance exceeding 12 sigma for each of them. We present results on angular scales from 3 arc-seconds to half a degree. The consistency of different statistical measures is demonstrated and confirms the lensing origin of the signal through tests that rely on the scalar nature of the gravitational potential. For Cold Dark Matter models we find $\\sigma_8 \\Omega_0^{0.6}=0.43^{+0.04}_{-0.05}$ at the 95% confidence level. The measurement over almost three decades of scale allows to discuss the effect of the shape of the power spectrum on the cosmological parameter estimation. The degeneracy on sigma_8-Omega_0 can be broken if priors on the shape of the linear power spectrum (that can be parameterized by Gamma) are assumed. For instance, with Gamma=0.21 and at the 95% confidence level, we obtain 0.6<sigma_8<1.1 and 0.2<Omega_0<0.5 for open models, and sigma_8>0.65 and Omega_0<0.4 for flat (Lambda-CDM) models. From the tangential/radial modes decomposition we can set an upper limit on the intrinsic shape alignment, which was recently suggested as a possible contribution to the lensing signal. Within the error bars, there is no detection of intrinsic shape alignment for scales larger than 1'.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 it