CFHT MegaPrime/MegaCam u-band source catalogue of the AKARI North Ecliptic Pole Wide field
Bibliographic record
Abstract
ABSTRACT The $AKARI$ infrared (IR) space telescope conducted two surveys (Deep and Wide) in the North Ecliptic Pole (NEP) field to find more than 100 000 IR sources using its infrared camera (IRC). IRC’s nine filters, which cover wavebands from 2 to 24 μm continuously, make $AKARI$ unique in comparison with other IR observatories such as $Spitzer$ or $WISE$. However, studies of the $AKARI$ NEP-Wide field sources had been limited due to the lack of follow-up observations in the ultraviolet (UV) and optical. In this work, we present the Canada–France–Hawaii Telescope MegaPrime/MegaCam u-band source catalogue of the $AKARI$ NEP-Wide field. The observations were taken in seven nights in 2015 and 2016, resulting in 82 observed frames covering 3.6 deg$^2$. The data reduction, image processing, and source extraction were performed in a standard procedure using the elixir pipeline and the astromatic software, and eventually 351 635 sources have been extracted. The data quality is discussed in two regions (shallow and deep) separately, due to the difference in the total integration time (4520 and 13 910 s). The 5$\sigma$ limiting magnitude, seeing full width at half-maximum, and the magnitude at 50 per cent completeness are 25.38 mag (25.79 mag in the deep region), 0.82 arcsec (0.94 arcsec), and 25.06 mag (25.45 mag), respectively. The u-band data provide us with critical improvements to photometric redshifts and UV estimates of the precious infrared sources from the $AKARI$ space telescope.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.007 |
| 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) | 0.019 | 0.010 |
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".