Extreme emission line galaxies detected in JADES <i>JWST</i>/NIRSpec – I. Inferred galaxy properties
Bibliographic record
Abstract
ABSTRACT Extreme emission line galaxies (EELGs) exhibit large equivalent widths (EW) in their rest-optical emission lines ([O iii]$\lambda 5007$ or H $\alpha$ rest-frame EW$\gt 750$ Å) which can be tied to a recent upturn in star formation rate (SFR), due to the sensitivity of the nebular line emission and the rest-optical continuum to young ($\lt 10$ Myr) and evolved stellar populations, respectively. By studying a sample of 85 star-forming galaxies (SFGs), spanning the redshift and magnitude interval $3 \lt z\lt 9.5$ and $-16\gt $M$\rm _{UV}\gt -21$, in the JWST Advanced Deep Extragalactic Survey (JADES) with NIRSpec/prism spectroscopy, we determine that SFGs initiate an EELG phase when entering a significant burst of star formation, with the highest EWs observed in EELGs with the youngest luminosity-weighted ages ($\lt 5$ Myr) and the highest burst intensity (those with the greatest excess between their current and long-term average SFR). We spectroscopically confirm that a greater proportion of SFGs are in an EELG phase at high redshift in our UV-selected sample ($61\pm 4~{{\ \rm per\ cent}}$ in our $z\gt 5.7$ high-redshift bin, compared to $23^{+4}_{-1}\%$ in our lowest redshift bin $3\lt z\lt 4.1$) due to the combined evolution of metallicity, ionization parameter, and star formation histories with redshift. We report that the EELGs within our sample exhibit a higher average ionization efficiency ($\log _{10}(\xi _\mathrm{ion}^\mathrm{HII}/{\rm erg^{-1}Hz}) =25.5\pm 0.2$) than the non-EELGs. High-redshift EELGs therefore comprise a population of efficient ionizing photon producers. Additionally, we report that 53 per cent (9/17) of EELGs at $z\gt 5.7$ have observed Ly $\alpha$ emission, potentially lying within large ionized regions. The high detection rate of Ly $\alpha$ emitters in our EELG selection suggests that the physical conditions associated with entering an EELG phase also promote the escape of Ly $\alpha$ photons.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".