The 0.1 <<i>z</i>< 1.65 evolution of the bright end of the [O ii] luminosity function
Bibliographic record
Abstract
We present the [Oii] (λλ3729,3726) luminosity function measured in the redshift range 0.1 <z< 1.65 with unprecedented depth and accuracy. Our measurements are based on medium resolution flux-calibrated spectra of emission line galaxies with the visual and near UV FOcal Reducer and low dispersion Spectrograph (FORS2) for the Very Large Telescope (VLT) of the European Southern Observatory (ESO) and with the SDSS-III/BOSS spectrograph. The FORS2 spectra and the corresponding catalog containing redshifts and line fluxes are released along with this paper. In this work we use a novel method to combine these surveys with GAMA, zCOSMOS, and VVDS, which have different target selection, producing a consistent weighting scheme to derive the [Oii] luminosity function. The[Oii] luminosity function is in good agreement with previous independent estimates. The comparison with two state-of-the-art semi-analytical models is good, which is encouraging for the production of mock catalogs of [Oii] flux limited surveys. We observe the bright end evolution over 8.5 Gyr: we measure the decrease of log L∗ from 42.4 erg/s at redshift 1.44 to 41.2 at redshift 0.165 and we find that the faint end slope flattens when redshift decreases. This measurement confirms the feasibility of the target selection of future baryonic acoustic oscillation surveys aiming at observing [Oii] flux limited samples.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".