SHARDS/CANDELS faint galaxies in GOODS-N (Merida+, 2023)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We base this work on the analysis of the CANDELS HST images combined with the 10.4m Gran Telescopio de Canarias (GTC) ultradeep imaging data from the Survey for High-z Absorption Red and Dead Sources (SHARDS; Perez-Gonzalez+ 2013, J/ApJ/762/46). We use version v3.0 of the mosaics provided by the GOODS HST/ACS Treasury Program (Giavalisco+ 2004, II/261; Grogin+ 2011ApJS..197...35G; Koekemoer+ 2011ApJS..197...36K) and the v1.0 data release for the WFC3/IR bands. The HST imaging reaches limiting magnitudes that range from 27.4 to 28.1mag with a point-spread function (PSF) FWHM that ranges from 0.1" to 0.2". SHARDS and SHARDS Frontier Fields (SHARDS-FF; Hernan-Caballero+ 2017ApJ...849...82H; Griffiths+ 2021MNRAS.508.3860G) are two large programs carried out using the OSIRIS (Cepa 1998) instrument to image the GOODS-N field and the MACS 1149 and A370 cluster fields, respectively, with 25 contiguous, medium-band filters (~15-16nm wide, except for two of the reddest ones). These data cover the spectral range between 0.5 and 0.95um. Additionally, we complement the HST and GTC data sets with NIR observations from the Wide-field InfraRed Camera (WIRCAM) at the Canada-France-Hawaii Telescope (CFHT; K band; Hsu+ 2019, J/ApJ/871/233), Spitzer/IRAC (3.6, 4.5, 5.8, and 8.0um bands; Dickinson+ 2003sptz.prop..196D; Ashby+ 2013, J/ApJ/769/80), and U, B images from SUBARU (Capak+ 2004, J/AJ/127/180). For the calculation of star formation rates (SFRs), we also take into account measurements from the Spitzer/MIPS 24 and 70um mosaics presented in Perez-Gonzalez+ (2008, J/ApJ/675/234), the Herschel PACS 100 and 160um, and the SPIRE 250, 350, and 500um catalogs described in Elbaz+ (2011, J/A+A/533/A119) and Magnelli+ (2013A&A...553A.132M).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it