Placing High-redshift Quasars in Perspective: A Catalog of Spectroscopic Properties from the Gemini Near Infrared Spectrograph–Distant Quasar Survey
Bibliographic record
Abstract
Abstract We present spectroscopic measurements for 226 sources from the Gemini Near Infrared Spectrograph–Distant Quasar Survey (GNIRS-DQS). Being the largest uniform, homogeneous survey of its kind, it represents a flux-limited sample (m i ≲ 19.0 mag, H ≲ 16.5 mag) of Sloan Digital Sky Survey (SDSS) quasars at 1.5 ≲ z ≲ 3.5 with a monochromatic luminosity ( ) at 5100 Å in the range of 1044–1046 erg s−1. A combination of the GNIRS and SDSS spectra covers principal quasar diagnostic features, chiefly the C iv λ1549, Mg ii λλ2798, 2803, Hβ λ4861, and [O iii] λλ4959, 5007 emission lines, in each source. The spectral inventory will be utilized primarily to develop prescriptions for obtaining more accurate and precise redshifts, black hole masses, and accretion rates for all quasars. Additionally, the measurements will facilitate an understanding of the dependence of rest-frame ultraviolet–optical spectral properties of quasars on redshift, luminosity, and Eddington ratio, and test whether the physical properties of the quasar central engine evolve over cosmic time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| 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 | 0.001 |
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".