Radio galaxies and their magnetic fields out to z ≤ 3
Bibliographic record
Abstract
We present polarization properties at 1.4 GHz of two separate extragalactic source populations: passive quiescent galaxies and luminous quasar-like galaxies. We use data from the Wide-Field Infrared Survey Explorer to determine the host galaxy population of the polarized extragalactic radio sources. The quiescent galaxies have higher percentage polarization, smaller radio linear size, and 1.4 GHz luminosity of 6 × 1021 < L1.4 < 7 × 1025 W Hz−1, while the quasar-like galaxies have smaller percentage polarization, larger radio linear size at radio wavelengths, and a 1.4 GHz luminosity of 9 × 1023 < L1.4 < 7 × 1028 W Hz−1, suggesting that the environment of the quasar-like galaxies is responsible for the lower percentage polarization. Our results confirm previous studies that found an inverse correlation between percentage polarization and total flux density at 1.4 GHz. We suggest that the population change between the polarized extragalactic radio sources is the origin of this inverse correlation and suggest a cosmic evolution of the space density of quiescent galaxies. Finally, we find that the extragalactic contributions to the rotation measures (RMs) of the nearby passive galaxies and the distant quasar-like galaxies are different. After accounting for the RM contributions by cosmological large-scale structure and intervening Mg ii absorbers we show that the distribution of intrinsic RMs of the distant quasar-like sources is at most four times as wide as the RM distribution of the nearby quiescent galaxies, if the distribution of intrinsic RMs of the WISE–Star sources itself is at least several rad m−2 wide.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".