Implications for unified schemes from the quasar fraction and emission-line luminosities in radio-selected samples
Bibliographic record
Abstract
We use a principal components analysis of radio-selected (3CRR, 6CE and 7CRS) active galactic nuclei (AGN) data sets to define two parameters related to low-frequency (151-MHz) radio luminosity L151 and [Oiii] luminosity L[Oiii]: a parameter α encoding the L151–L[Oiii] correlation and a parameter β encoding scatter about this correlation. We describe methods for constructing generalized luminosity functions (GLFs) based on α, β, redshift and schemes for unifying quasars and radio galaxies. These GLFs can be used to generate radio luminosity functions (RLFs) which improve on those of Willott et al. (2001a), mostly because they incorporate scatter and are therefore much smoother. Luminosity-dependent unified schemes (e.g. a receding-torus scheme) have been invoked to explain the low quasar-to-radio galaxy fraction at low α and the differences in emission-line luminosities of radio quasars and radio galaxies. With the constraints of the 3CRR, 6CE and 7CRS data sets and radio source counts, our GLF approach was used to determine whether a receding-torus-like scheme is required if there are two populations of radio sources: one at low α, consisting of ‘starved AGN’; the other at high α, consisting of ‘Eddington-tuned AGN’. Because of the overlap between these two populations and the effects of the β parameter, schemes with or without a receding torus can produce a low quasar fraction at low α and differences in [Oiii] luminosity between radio galaxies and quasars. The receding torus may be a physical process important in one or more populations of radio sources, but this is not yet proved either by the quasar fraction or the emission-line properties of radio-selected samples.
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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 | 0.038 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".