Comparing extragalactic megahertz-peaked spectrum and gigahertz-peaked spectrum sources
Bibliographic record
Abstract
Recent sensitive wide-field radio surveys, such as the LOFAR Two-metre Sky Survey (LoTSS), the LOFAR LBA Sky Survey (LoLSS), and the Very Large Array Sky Survey (VLASS), enable the selection of statistically large samples of peaked spectrum (PS) sources. PS sources are radio sources that have a peak in their radio continuum spectrum and are observed to be compact. They are often considered to be the precursors to large radio galaxies. We present a sample of 8032 gigahertz-peaked spectrum (GPS) sources with spectral turnovers near 1400 MHz, and a sample of 506 megahertz-peaked spectrum (MPS) sources with turnovers near 144 MHz. Our GPS sample is over five times larger than any previously known sample of PS sources. These large sample sizes allow us to make a robust comparison between GPS sources and MPS sources, such that we can investigate the differences between these types of sources, and study their lifetimes. The shape of the source counts of both samples match that of the general radio-loud active galactic nuclei (AGN) samples, scaled down by a factor 44 ± 2 for the MPS sample, and a factor 28 ± 1 for the GPS sample. Assuming no cosmological evolution, these offsets imply that both MPS and GPS sources have a shorter duration than general radio-loud AGN, with MPS sources having an ≈1.6 times shorter lifespan than GPS sources. The shorter duration of MPS sources relative to GPS sources can be explained by the transition between GPS and MPS sources coinciding with the jet breakout phase of PS sources, such that GPS sources traverse through the surrounding medium at a lower speed than MPS sources. Such evolution has been observed in simulations of PS source evolution.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".