The OTELO survey
Bibliographic record
Abstract
Aims. We take advantage of the capability of the OTELO survey to obtain the Hαluminosity function (LF) at z ∼ 0.40. Because of the deepest coverage of OTELO, we are able to determine the faint end of the LF, and thus better constrain the star formation rate and the number of galaxies at low luminosities. The AGN contribution to this LF is estimated as well. Methods. We make use of the multiwavelength catalogue of objects in the field compiled by the OTELO survey, which is unique in terms of minimum flux and equivalent width. We also take advantage of the pseudo-spectra built for each source, which allow the identification of emission lines and the discrimination of different types of objects. Results. The Hαluminosity function atz ∼ 0.40 is obtained, which extends the current faint end by almost 1 dex, reaching minimal luminosities of log10Llim = 38.5 erg s−1(or ∼0.002 M⊙yr−1). The AGN contribution to the total Hαluminosity is estimated. We find that no AGN should be expected below a luminosity of log10L = 38.6 erg s−1. From the sample of non-AGN (presumably, pure SFG) atz ∼ 0.40 we estimated a star formation rate density ofρSFR = 0.012 ± 0.005M⊙ yr−1 Mpc−3.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.034 | 0.006 |
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".