<i>z</i>∼ 7 GALAXY CANDIDATES FROM NICMOS OBSERVATIONS OVER THE HDF-SOUTH AND THE CDF-SOUTH AND HDF-NORTH GOODS FIELDS
Bibliographic record
Abstract
We use ∼88 arcmin 2 of deep (≳26.5 mag at 5σ) NICMOS data over the two GOODS fields and the HDF-South to conduct a search for bright z ≳ 7 galaxy candidates. This search takes advantage of an efficient preselection over 58 arcmin 2 of NICMOS H 160 -band data where only plausible z ≳ 7 candidates are followed up with NICMOS J 110 -band observations. ∼248 arcmin 2 of deep ground-based near-infrared data (≳25.5 mag, 5σ) are also considered in the search. In total, we report 15 z 850 -dropout candidates over this area—7 of which are new to these search fields. Two possible z ∼ 9 J 110 -dropout candidates are also found, but seem unlikely to correspond to z ∼ 9 galaxies (given the estimated contamination levels). The present z ∼ 9 search is used to set upper limits on the prevalence of such sources. Rigorous testing is undertaken to establish the level of contamination of our selections by photometric scatter, low-mass stars, supernovae, and spurious sources. The estimated contamination rate of our z ∼ 7 selection is ∼24%. Through careful simulations, the effective volume available to our z ≳ 7 selections is estimated and used to establish constraints on the volume density of luminous ( L * z = 3 , or ∼−21 mag) galaxies from these searches. We find that the volume density of luminous star-forming galaxies at z ∼ 7 is 13 +8 −5 times lower than at z ∼ 4 and >25 times lower (1σ) at z ∼ 9 than at z ∼ 4. This is the most stringent constraint yet available on the volume density of ≳ L * z = 3 galaxies at z ∼ 9. The present wide-area, multi-field search limits cosmic variance to ≲20%. The evolution we find at the bright end of the UV LF is similar to that found from recent Subaru Suprime-Cam, HAWK-I or ERS WFC3/IR searches. The present paper also includes a complete summary of our final z ∼ 7 z 850 -dropout sample (18 candidates) identified from all NICMOS observations to date (over the two GOODS fields, the HUDF, galaxy clusters).
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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 | 0.001 |
| 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 | 0.000 |
| 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".