Gemini Near Infrared Spectrograph–Distant Quasar Survey: Augmented Spectroscopic Catalog and a Prescription for Correcting UV-based Quasar Redshifts
Bibliographic record
Abstract
Abstract Quasars at z ≳ 1 most often have redshifts measured from rest-frame ultraviolet emission lines. One of the most common such lines, C iv λ1549, shows blueshifts up to ≈5000 km s−1 and in rare cases even higher. This blueshifting results in highly uncertain redshifts when compared to redshift determinations from rest-frame optical emission lines, e.g., from the narrow [O iii] λ5007 feature. We present spectroscopic measurements for 260 sources at 1.55 ≲ z ≲ 3.50 having −28.0 ≲ M i ≲ − 30.0 mag from the Gemini Near Infrared Spectrograph–Distant Quasar Survey (GNIRS-DQS) catalog, augmenting the previous iteration, which contained 226 of the 260 sources whose measurements are improved upon in this work. We obtain reliable systemic redshifts based on [O iii] λ5007 for a subset of 121 sources, which we use to calibrate prescriptions for correcting UV-based redshifts. These prescriptions are based on a regression analysis involving C iv full-width-at-half-maximum intensity and equivalent width, along with the UV continuum luminosity at a rest-frame wavelength of 1350 Å. Applying these corrections can improve the accuracy and the precision in the C iv-based redshift by up to ∼850 km s−1 and ∼150 km s−1, respectively, which correspond to ∼8.5 and ∼1.5 Mpc in comoving distance at z = 2.5. Our prescriptions also improve the accuracy of the best available multifeature redshift determination algorithm by ∼100 km s−1, indicating that the spectroscopic properties of the C iv emission line can provide robust redshift estimates for high-redshift quasars. We discuss the prospects of our prescriptions for cosmological and quasar studies utilizing upcoming large spectroscopic surveys.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".