ZEN2: a narrow<i>J</i>-band search for<i>z</i>∼ 9 Lyα emitting galaxies directed towards three lensing clusters
Bibliographic record
Abstract
We present the results of a continuing survey to detect Lyα emitting galaxies at redshifts z∼ 9: the ‘z equals nine’ (ZEN) survey. We have obtained deep VLT Infrared Spectrometer and Array Camera observations in the narrow J-band filter NB119 directed towards three massive lensing clusters: Abell clusters 1689, 1835 and 114. The foreground clusters provide a magnified view of the distant Universe and permit a sensitive test for the presence of very high redshift galaxies. We search for z∼ 9 Lyα emitting galaxies displaying a significant narrow-band excess relative to accompanying J-band observations that remain undetected in Hubble Space Telescope (HST)/Advanced Camera for Surveys (ACS) optical images of each field. No sources consistent with this criterion are detected above the unlensed 90 per cent point-source flux limit of the narrow-band image, FNB= 3.7 × 10−18erg s−1cm−2. To date, the total coverage of the ZEN survey has sampled a volume at z∼ 9 of approximately 1700 comoving Mpc3 to a Lyα emission luminosity of 1043erg s−1. We conclude by considering the prospects for detecting z∼ 9 Lyα emitting galaxies in light of both observed galaxy properties at z < 7 and simulated populations at z > 7.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".