Radio source calibration for the Very Small Array and other cosmic microwave background instruments at around 30 GHz
Bibliographic record
Abstract
Accurate calibration of data is essential for the current generation of cosmic microwave background (CMB) experiments. Using data from the Very Small Array (VSA), we describe procedures which will lead to an accuracy of 1 per cent or better for experiments such as the VSA and CBI. Particular attention is paid to the stability of the receiver systems, the quality of the site and frequent observations of reference sources. At 30 GHz the careful correction for atmospheric emission and absorption is shown to be essential for achieving 1 per cent precision. The sources for which a 1 per cent relative flux density calibration was achieved included Cas A, Cyg A, Tau A and NGC 7027 and the planets Venus, Jupiter and Saturn. A flux density, or brightness temperature in the case of the planets, was derived at 33 GHz relative to Jupiter which was adopted as the fundamental calibrator. A spectral index at ∼30 GHz is given for each. Cas A, Tau A, NGC 7027 and Venus were examined for variability. Cas A was found to be decreasing at 0.394 ± 0.019 per cent yr−1 over the period 2001 March to 2004 August. In the same period Tau A was decreasing at 0.22 ± 0.07 per cent yr−1. A survey of the published data showed that the planetary nebula NGC 7027 decreased at 0.16 ± 0.04 per cent yr−1 over the period 1967–2003. Venus showed an insignificant (1.5 ± 1.3 per cent) variation with Venusian illumination. The integrated polarization of Tau A at 33 GHz was found to be 7.8 ± 0.6 per cent at position angle =148°± 3°.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".