Error estimation for the MAP experiment
Bibliographic record
Abstract
We report here the first full sky component separation and CMB power spectrum estimation using a Wiener filtering technique on simulated data from the upcoming MAP experiment, set to launch in early 2001. The simulations included contributions from the three dominant astrophysical components expected in the five MAP spectral bands, namely CMB radiation, Galactic dust, and synchrotron emission. We assumed a simple homogeneous and isotropic white noise model and performed our analysis up to a spherical harmonic multipole lmax=512 on the fraction of the sky defined by b>20 degrees. We find that the reconstruction errors are reasonably well fitted by a Gaussian with an rms of 24 $\\mu $K, but with significant deviations in the tails. Our results further support the predictions on the resulting CMB power spectrum of a previous estimate by Bouchet and Gispert (1999), which entailed a number of assumptions this work removes.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".