The Infrared Medium-deep Survey. IX. Discovery of Two New z ∼ 6 Quasars and Space Density Down to M <sub>1450</sub> ∼ −23.5 mag
Bibliographic record
Abstract
Abstract We present the result of the Infrared Medium-deep Survey (IMS) z ∼ 6 quasar survey, using the combination of the IMS near-infrared images and the Canada–France–Hawaii Telescope Legacy Survey optical images. The traditional color selection method results in 25 quasar candidates over 86 deg2. We introduce the corrected Akaike information criterion (AICc) with the high-redshift quasar and late-type star models to prioritize the candidates efficiently. Among the color-selected candidates, seven plausible candidates finally passed the AICc selection, of which three are known quasars at z ∼ 6. The follow-up spectroscopic observations for the remaining four candidates were carried out, and we confirmed that two out of four are z ∼ 6 quasars. With this complete sample, we revisited the quasar space density at z ∼ 6 down to M 1450 ∼ −23.5 mag. Our result supports the low quasar space density at the luminosity where the quasar’s ultraviolet ionizing emissivity peaks, favoring a minor contribution of quasars to the cosmic reionization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".