XQ-100: A legacy survey of one hundred 3.5 ≲<i>z</i>≲ 4.5 quasars observed with VLT/X-shooter
Bibliographic record
Abstract
We describe the execution and data reduction of the European Southern Observatory Large Programme “Quasars and their absorption lines: a legacy survey of the high-redshift Universe with VLT/X-shooter” (hereafter “XQ-100”). XQ-100 has produced and made publicly available a homogeneous and high-quality sample of echelle spectra of 100 quasars (QSOs) at redshifts z ≃ 3.5–4.5 observed with full spectral coverage from 315 to 2500 nm at a resolving power ranging from R ~ 4000 to 7000, depending on wavelength. The median signal-to-noise ratios are 33, 25 and 43, as measured at rest-frame wavelengths 1700, 3000 and 3600 Å, respectively. This paper provides future users of XQ-100 data with the basic statistics of the survey, along with details of target selection, data acquisition and data reduction. The paper accompanies the public release of all data products, including 100 reduced spectra. XQ-100 is the largest spectroscopic survey to date of high-redshift QSOs with simultaneous rest-frame UV/optical coverage, and as such enables a wide range of extragalactic research, from cosmology and galaxy evolution to AGN astrophysics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".