ELLIPTICITY ANALYSIS OF THE BOOMERanG CMB MAPS
Bibliographic record
Abstract
The properties of the Cosmic Microwave Background (CMB) maps carry valuable cosmological information. Here we report the results of the analysis of ellipticity of the hot and cold CMB anisotropy spots in the BOOMERanG 150 GHz map. We carried out this analysis for the map obtained by summing independent measurement channels (signal plus noise map) and for a comparison map (noise only map) obtained by differencing the same channels. The anisotropy areas (spots) have been identified for both maps for various temperature thresholds. The orientation (obliquity) of the spots is random for both maps. We computed the mean elongation of spots obtained from the maps at a given temperature threshold using a simple estimator. We found that for the sum map there is a region of temperature thresholds where the average elongation is not dependent on the threshold. Its value is $\\sim$ 2.3 for cold areas and $\\sim$ 2.2 for hot areas. The bias of the estimator is $\\simlt +0.4$. The presence of noise also biases the ellipticity by $\\simlt +0.3$. These biases have not been subtracted in the results quoted above. The threshold independent and random obliquity behaviour in the sum map is stable against pointing reconstruction accuracy and noise level of the data, thus confirming that these are actual properties of the dataset. In the sum map the anisotropy areas are elongated more homogeneously than in the difference map. Analogous elongation properties of CMB anisotropies had been detected for COBE-DMR 4 year data.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".