The space density of<i>z</i> > 4 blazars
Bibliographic record
Abstract
High-redshift blazars are an important class of active galactic nuclei (AGN) that can provide an independent estimate of the supermassive black hole mass function in high-redshift radio-loud AGN without the bias due to absorption along the line of sight. Using the Cosmic Lens All Sky Survey (CLASS), we built a complete radio flux-limited sample of high-redshift (z > 4) blazars suitable for statistical studies. By combining dedicated optical observations and the SDSS spectroscopic database, we obtained a sample of 26 blazar candidates with a spectroscopic redshift above 4. On the basis of their radio spectrum, we distinguish between blazars and QSO with a Gigahertz Peaked Spectrum (GPS) like spectrum. Out of the 18 confirmed blazars 14 constitute a completely identified, flux-limited sample down to a magnitude of 21 (AB). Using this complete sample, we derive a space density of blazars with 4 < z < 5.5 of ρ = 0.13|$^{+0.05}_{-0.03}$| Gpc−3. This is the first actual estimate of the blazar space density in this range of redshift. This value is in good agreement with the extrapolation of the luminosity function and cosmological evolution based on a sample of flat-spectrum radio quasars selected at lower redshifts and it is consistent with a cosmological evolution peaking at z ∼ 2 similar to radio-quiet QSO. We do not confirm, instead, the presence of a peak at z ∼ 4 in the space density evolution, recently suggested using an X-ray selected sample of blazars. It is possible that this extreme peak of the evolution is present only among the most luminous blazars.
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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) | 0.007 | 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".