Comparing and combining the Saskatoon, QMAP and COBE CMB maps
Bibliographic record
Abstract
We present a method for comparing and combining maps with different resolutions and beam shapes, and apply it to the Saskatoon, QMAP and COBE/DMR data sets. Although the Saskatoon and QMAP maps detect signal at the 21 sigma and 40 sigma levels, respectively, their difference is consistent with pure noise, placing strong limits on possible systematic errors. In particular, we obtain quantitative upper limits on relative calibration and pointing errors. Splitting the combined data by frequency shows similar consistency between the Ka- and Q-bands, placing limits on foreground contamination. The visual agreement between the maps is equally striking. Our combined QMAP+Saskatoon map, nicknamed QMASK, is publicly available at www.hep.upenn.edu/~xuyz/qmask.html together with its 6495x6495 noise covariance matrix. This thoroughly tested data set covers a large enough area (648 square degrees -- currently the largest degree-scale map available) to allow a statistical comparison with COBE/DMR, showing good agreement.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".