A population of high-redshift type 2 quasars - I. Selection criteria and optical spectra
Bibliographic record
Abstract
We discuss the relative merits of mid-infrared and X-ray selection of type 2 quasars. We describe the mid-infrared, near-infrared and radio selection criteria used to find a population of redshift z∼ 2 type 2 quasars which we previously argued suggests that most supermassive black hole growth in the Universe is obscured. We present the optical spectra obtained from the William Herschel Telescope, and we compare the narrow emission-line luminosity, radio luminosity and maximum size of jets to those of objects from radio-selected samples. This analysis suggests that these are genuine radio-quiet type 2 quasars, albeit the radio-bright end of this population. We also discuss the possibility of two different types of quasar obscuration, which could explain how the ∼2–3:1 ratio of type 2 to type 1 quasars preferred by modelling our population can be reconciled with the ∼1:1 ratio predicted by unified schemes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".