Bibliographic record
Abstract
Context. The evolution of galaxies through cosmic time is studied observationally by means of extragalactic surveys. The usefulness of these surveys is greatly improved by increasing the cosmological volume, in either depth or area, and by observing the same targets in different wavelength ranges. A multi-wavelength approach using different observational techniques can compensate for observational biases. Aims. The OTELO survey aims to provide the deepest narrow-band survey to date in terms of minimum detectable flux and emission line equivalent width in order to detect the faintest extragalactic emission line systems. In this way, OTELO data will complements other broad-band, narrow-band, and spectroscopic surveys. Methods. The red tunable filter of the OSIRIS instrument on the 10.4 m Gran Telescopio Canarias (GTC) is used to scan a spectral window centred at 9175 Å, which is free from strong sky emission lines, with a sampling interval of 6 Å and a bandwidth of 12 Å in the most deeply explored EGS region. Careful data reduction using improved techniques for sky ring subtraction, accurate astrometry, photometric calibration, and source extraction enables us to compile the OTELO catalogue. This catalogue is complemented with ancillary data ranging from deep X-ray to far-infrared, including high resolution HST images, which allow us to segregate the different types of targets, derive precise photometric redshifts, and obtain the morphological classification of the extragalactic objects detected. Results. The OTELO multi-wavelength catalogue contains 11 237 entries and is 50% complete at AB magnitude 26.38. Of these sources, 6600 have photometric redshifts with an uncertaintyδ zphotbetter than 0.2 (1+zphot). A total of 4336 of these sources correspond to preliminary emission line candidates, which are complemented by 81 candidate stars and 483 sources that qualify as absorption line systems. The OTELO survey results will be released to the public on the second half of 2019.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.076 | 0.022 |
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".