Bibliographic record
Abstract
Aims. We present the main steps that will be taken to extract Hα emission flux from Javalambre Photometric Local Universe Survey (J-PLUS) photometric data. Methods. For galaxies with z ≲ 0.015, the Hα+[N ii] emission is covered by the J-PLUS narrow-band filter F660. We explore three different methods to extract the Hα + [N ii] flux from J-PLUS photometric data: a combination of a broad-band and a narrow-band filter (r′ and F660), two broad-band and a narrow-band filter (r′, i′ and F660), and an SED-fitting based method using eight photometric points. To test these methodologies, we simulated J-PLUS data from a sample of 7511 SDSS spectra with measured Hα flux. Based on the same sample, we derive two empirical relations to correct the derived Hα+[N ii] flux from dust extinction and [N ii] contamination. Results. We find that the only unbiased method is the SED-fitting based method. The combination of two filters underestimates the measurements of the Hα + [N ii] flux by 22%, while the three filters method are underestimated by 9%. We study the error budget of the SED-fitting based method and find that, in addition to the photometric error, our measurements have a systematic uncertainty of 4.3%. Several sources contribute to this uncertainty: the differences between our measurement procedure and that used to derive the spectroscopic values, the use of simple stellar populations as templates, and the intrinsic errors of the spectra, which were not taken into account. Apart from that, the empirical corrections for dust extinction and [N ii] contamination add an extra uncertainty of 14%. Conclusions. Given the J-PLUS photometric system, the best methodology to extract Hα + [N ii] flux is the SED-fitting based method. Using this method, we are able to recover reliable Hα fluxes for thousands of nearby galaxies in a robust and homogeneous way. Moreover, each stage of the process (emission line flux, dust extinction correction, and [N ii] decontamination) can be decoupled and improved in the future. This method ensures reliable Hα measurements for many studies of galaxy evolution, from the local star formation rate density, to 2D studies in spatially well-resolved galaxies or the study of environmental effects, up to mr′ = 21.8 (AB; 3σ detection of Hα+[N ii] emission).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.042 |
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".