THE SDSS-IV EXTENDED BARYON OSCILLATION SPECTROSCOPIC SURVEY: QUASAR TARGET SELECTION
Bibliographic record
Abstract
As part of the Sloan Digital Sky Survey (SDSS) IV the extended Baryon Oscillation Spectroscopic Survey ( eBOSS ) will improve measurements of the cosmological distance scale by applying the Baryon Acoustic Oscillation (BAO) method to quasar samples. eBOSS will adopt two approaches to target quasars over 7500 deg 2 . First, a "CORE" quasar sample will combine the optical selection in ugriz using a likelihood-based routine called XDQSOz , with a mid-IR-optical color cut. eBOSS CORE selection (to g < 22 or r < 22) should return ∼70 deg −2 quasars at redshifts 0.9 < z < 2.2 and ∼7 deg −2 z > 2.1 quasars. Second, a selection based on variability in multi-epoch imaging from the Palomar Transient Factory should recover an additional ∼3–4 deg −2 z > 2.1 quasars to g < 22.5. A linear model of how imaging systematics affect target density recovers the angular distribution of eBOSS CORE quasars over 96.7% (76.7%) of the SDSS north (south) Galactic Cap area. The eBOSS CORE quasar sample should thus be sufficiently dense and homogeneous over 0.9 < z < 2.2 to yield the first few-percent-level BAO constraint near eBOSS quasars at z > 2.1 will be used to improve BAO measurements in the Ly α Forest. Beyond its key cosmological goals, eBOSS should be the next-generation quasar survey, comprising >500,000 new quasars and >500,000 uniformly selected spectroscopically confirmed 0.9 < z < 2.2 quasars. At the conclusion of eBOSS , the SDSS will have provided unique spectra for more than 800,000 quasars.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".