ZEN and the search for high-redshift galaxies
Bibliographic record
Abstract
We present the ZEN (z equals nine) survey: a deep, narrow J-band search for proto-galactic Lya emission at redshifts z=9. In the first phase of the survey, dubbed ZEN1, we combine an exceptionally deep image of the Hubble Deep Field South, obtained using a narrow band filter centred on the wavelength 1.187 microns, with existing deep, broad band images covering optical to near infrared wavelengths. Candidate z=9 Lya-emitting galaxies display a significant narrow band excess relative to the Js-band that are undetected at optical wavelengths. We detect no sources consistent with this criterion to the 90% point source flux limit of the NB image, F_NB = 3.28e-18 ergs/s/cm2. The survey selection function indicates that we have sampled a volume of approximately 340 h^{-3} Mpc3 to a Lya emission luminosity of 10e43 h^{-2} ergs/s. When compared to the predicted properties of z=9 galaxies based upon no evolution of observed z=6 Lya-emitting galaxies, the `volume shortfall' of the current survey, i.e. the volume required to detect this putative population, is a factor of at least 8 to 10. We also discuss continuing narrow J-band imaging surveys that will reduce the volume shortfall factor to the point where the no-evolution prediction from z=6 is probed in a meaningful manner.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".