The Next Generation Virgo Cluster Survey. XV. The photometric estimation for background sources
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Bibliographic record
Abstract
The Next Generation Virgo Cluster Survey (NGVS) is an optical imaging survey covering 104 deg2 centered on the Virgo cluster. Currently, the complete survey area has been observed in the u∗ giz bands and one third in the r band. We present the photometric redshift estimation for the NGVS background sources. After a dedicated data reduction, we perform accurate photometry, with special attention to precise color measurements through pointspread function homogenization. We then estimate the photometric redshifts with the Le Phare and BPZ codes. We add a new prior that extends to iAB = 12.5 mag. When using the u∗griz bands, our photometric redshifts for 15.5mag ≤ i ≲ 23 mag or zphot ≲ 1 galaxies have a bias |Äz| < 0.02, less than 5% outliers, a scatter óoutl.rej., and an individual error on zphot that increases with magnitude (from 0.02 to 0.05 and from 0.03 to 0.10, respectively).When using the u∗giz bands over the same magnitude and redshift range, the lack of the r band increases the uncertainties in the 0.3 ≲ zphot ≲ 0.8 range (-0.05 < Äz < -0.02, óoutl.rej ∼ 0.06, 10%-15% outliers, and zphot.err. ∼ 0.15). We also present a joint analysis of the photometric redshift accuracy as a function of redshift and magnitude. We assess the quality of our photometric redshifts by comparison to spectroscopic samples and by verifying that the angular auto- and cross-correlation function w(θ) of the entire NGVS photometric redshift sample across redshift bins is in agreement with the expectations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it