J-PLUS: Measuring H<i>α</i> emission line fluxes in the nearby universe
Bibliographic record
Abstract
In this paper we aim to validate a methodology designed to obtain Hα emission line fluxes from J-PLUS photometric data. J-PLUS is a multi narrow-band filter survey carried out with the 2 deg2 field of view T80Cam camera, mounted on the JAST/T80 telescope in the OAJ, Teruel, Spain. The information of the twelve J-PLUS bands, including the J0660 narrow-band filter located at rest-frame Hα, is used over the first 42 deg2 observed to retrieve de-reddened and [NII] decontaminated Hα emission line fluxes of 46 star-forming regions with previous SDSS and/or CALIFA spectroscopic information. The agreement between the J-PLUS Hα fluxes and those obtained with spectroscopic data is remarkable, finding a median comparison ratio with a scatter of $ \mathcal{R}\,{=}\,F^{\mathrm{J-PLUS}}_{\mathrm{H\alpha}}/F^{\mathrm{spec}}_{\mathrm{H\alpha}}\,{=}\,1.05\,{\pm}\,0.25 $. This demonstrates that it is possible to retrieve reliable Hα emission line fluxes from J-PLUS photometric data. With an expected area of thousands of square degrees upon completion, the J-PLUS dataset will allow the study of several star formation science cases in the nearby universe, as the spatially resolved star formation rate of nearby galaxies at z ≤ 0.015, and how it is influenced by the environment, morphology, stellar mass, and nuclear activity. As an illustrative example, the close pair of interacting galaxies NGC 3994 and NGC 3995 is analysed, finding an enhancement of the star formation rate not only in the centre, but also in outer parts of the disk of NGC 3994.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.002 |
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".