AllBRICQS: The All-sky BRIght, Complete Quasar Survey
Bibliographic record
Abstract
Abstract We describe the first results from the All-sky BRIght, Complete Quasar Survey (AllBRICQS), which aims to discover the last remaining optically bright quasars. We present 156 spectroscopically confirmed quasars (140 newly identified) having $|b|>10^{\circ}$ . 152 of the quasars haveGaiaDR3 magnitudes brighter than $B_{P}=16.5$ or $R_{P}=16$ mag, while four are slightly fainter. The quasars span a redshift range of $z=0.07-3.93$ . In particular, we highlight the properties of J0529-4351 at $z=3.93$ , which, if unlensed, is one of the most intrinsically luminous quasars in the Universe. The AllBRICQS sources have been selected by combining data from theGaiaandWISEall-sky satellite missions, and we successfully identify quasars not flagged as candidates byGaiaData Release 3. We expect the completeness to be $\approx$ 96% within our magnitude and latitude limits, while the preliminary results indicate a selection purity of $\approx$ 96%. The optical spectroscopy used for source classification will also enable detailed quasar characterisation, including black hole mass measurements and identification of foreground absorption systems. The AllBRICQS sources will greatly enhance the number of quasars available for high-signal-to-noise follow-up with present and future facilities.
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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 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.008 | 0.003 |
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".