S-band Polarization All-Sky Survey (S-PASS): survey description and maps
Bibliographic record
Abstract
Abstract We present the S-Band Polarization All Sky Survey (S-PASS), a survey of polarized radio emission over the southern sky at Dec. <−1° taken with the Parkes radio telescope at 2.3 GHz. The main aim was to observe at a frequency high enough to avoid strong depolarization at intermediate Galactic latitudes (still present at 1.4 GHz) to study Galactic magnetism, but low enough to retain ample signal-to-noise ratio (S/N) at high latitudes for extragalactic and cosmological science. We developed a new scanning strategy based on long azimuth scans and a corresponding map-making procedure to make recovery of the overall mean signal of Stokes Q and U possible, a long-standing problem with polarization observations. We describe the scanning strategy, map-making procedure and validation tests. The overall mean signal is recovered with a precision better than 0.5 per cent. The maps have a mean sensitivity of 0.81 mK on beam-size scales and show clear polarized signals, typically to within a few degrees of the Galactic plane, with ample S/N everywhere (the typical signal in low-emission regions is 13 mK and 98.6 per cent of pixels have S/N > 3). The largest depolarization areas are in the inner Galaxy, associated with the Sagittarius Arm. We have also computed a rotation measure map combining S-PASS with archival data from the Wilkinson Microwave Anisotropy Probe (WMAP) and Planck experiments. A Stokes I map has been generated, with sensitivity limited to the confusion level of 9 mK.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.011 |
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".