<i>Euclid</i> preparation
Bibliographic record
Abstract
The Cosmic Dawn Survey (DAWN survey) provides multiwavelength (UV/optical to mid-IR) data across the combined 59 deg2 of the Euclid Deep and Auxiliary fields (EDFs and EAFs). In this work, the first public data release from the DAWN survey is presented. The catalogues made available herein consist of a subset of the full DAWN survey that includes two EDFs: EDF North (EDF-N) and EDF Fornax (EDF-F). Each field has been covered by the ongoing Hawaii Twenty Square Degree Survey (H20), which includes imaging from the CFHT MegaCam in the u filter and from the Subaru Hyper Suprime-Cam (HSC) in the griz filters. Each field has been further covered by Spitzer/IRAC 3.6–4.5µm imaging spanning 10 deg2 and reaching ~25 mag AB (5σ). All present H20 imaging and all publicly available imaging from the aforementioned facilities were combined with the deep Spitzer/IRAC data to create source catalogues spanning a total area of 16.87 deg2 in EDF-N and 2.85 deg2 in EDF-F for this first release. These catalogues are referred to as the ‘pre-launch’ (PL), as Euclid data is not yet public for these fields and therefore it is not included. Photometry was measured from these multiwavelength data using The Farmer, a novel and well validated model-based photometry code. Photometric redshifts and stellar masses were computed using two independent codes for modelling spectral energy distributions: EAZY and LePhare. Photometric redshifts show good agreement with spectroscopic redshifts (σNMAD ~ 0.5, η < 8% at i < 25). Number counts, photometric redshifts and stellar masses were further validated in comparison to the COSMOS2020 catalogue. The DAWN survey PL catalogues are designed to be of immediate use in these two EDFs and will be continuously updated and made available as both new ground-based data and spaced-based data from Euclid are acquired and made public. Future data releases will provide catalogues of all EDFs and EAFs and include Euclid data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.177 | 0.230 |
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".