ASTRODEEP-JWST: NIRCam-HST multi-band photometry and redshifts for half a million sources in six extragalactic deep fields
Bibliographic record
Abstract
Aims . We present a set of photometric catalogues primarily aimed at providing the community with a comprehensive database for the study of galaxy populations in the high-redshift Universe. The set gathers data from eight JWST NIRCam observational programs, targeting the Abell 2744 (GLASS-JWST, UNCOVER, DDT2756, and GO3990), EGS (CEERS), COSMOS and UDS (PRIMER), and the GOODS North and South (JADES and NGDEEP) deep fields. This dataset covers a total area of ≃0.2 sq. degrees. Methods . We obtained photometric estimates by means of well-established techniques, including tailored improvements designed to enhance the performance on the specific dataset. We also included new measurements from HST archival data, spanning 16 bands from 0.44 to 4.44 µm. Results . A grand total of ~530 thousand sources were detected on stacks of NIRCam 3.56 and 4.44 µm mosaics. We assessed the photometric accuracy by comparing fluxes and colours against archival catalogues. We also provide photometric redshift estimates, statistically validated against a large set of robust spectroscopic data. Conclusions . The catalogues are publicly available on the A STRODEEP website.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.015 |
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".