A broad-band spectro-polarimetric view of the NVSS rotation measure catalogue – II. Effects of off-axis instrumental polarization
Bibliographic record
Abstract
Abstract The NRAO VLA Sky Survey (NVSS) rotation measure (RM) catalogue has enabled numerous studies in cosmic magnetism, and will continue being a unique data set complementing future polarization surveys. Robust comparisons with these new surveys will however require further understandings in the systematic effects present in the NVSS RM catalogue. In this paper, we make careful comparisons between our new on-axis broad-band observations with the Karl G. Jansky Very Large Array and the NVSS RM results for 23 sources. We found that two unpolarized sources were reported as polarized at about 0.5 per cent level in the RM catalogue, and noted significant differences between our newly derived RM values and the catalogue values for the remaining 21 sources. These discrepancies are attributed to off-axis instrumental polarization in the NVSS RM catalogue. By adopting the 0.5 per cent above as the typical off-axis instrumental polarization amplitude, we quantified its effect on the reported RMs with a simulation, and found that on average the RM uncertainties in the catalogue have to be increased by ${\approx } 10\, {{\ \rm per\ cent}}$ to account for the off-axis instrumental polarization effect. This effect is more substantial for sources with lower fractional polarization, and is a function of the source’s true RM. Moreover, the distribution of the resulting RM uncertainty is highly non-Gaussian. With the extra RM uncertainty incorporated, we found that the RM values from the two observations for most (18 out of 21) of our polarized targets can be reconciled. The remaining three are interpreted as showing hints of time variabilities in RM.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".