JADES: The emergence and evolution of Ly<i>α</i> emission and constraints on the intergalactic medium neutral fraction
Bibliographic record
Abstract
The rest-frame UV recombination emission line Lyα can be powered by ionising photons from young massive stars in star-forming galaxies, but the fact that it can be resonantly scattered by neutral gas complicates its interpretation. For reionisation-era galaxies, a neutral intergalactic medium will scatter Lyα from the line of sight, making Lyα a useful probe of the neutral fraction evolution. Here, we explore Lyα in JWST/NIRSpec spectra from the ongoing JADES programme, which targets hundreds of galaxies in the well-studied GOODS-S and GOODS-N fields. These sources are UV-faint (−20.4 < MUV < −16.4) and thus represent a poorly explored class of galaxy. We fitted the low spectral resolution spectra (R ∼ 100) of a subset of 84 galaxies in GOODS-S with zspec > 5.6 (as derived with optical lines) with line and continuum models to search for significant line emission. Through exploration of the R100 data, we find evidence for Lyα in 17 sources. This sample allowed us to place observational constraints on the fraction of galaxies with Lyα emission in the redshift range 5.6 < z < 7.5, with a decrease from z = 6 to z = 7. We also find a positive correlation between the Lyα equivalent width and MUV, as seen in other samples. We used these results to estimate the neutral gas fraction at z ∼ 7, and our estimates are in agreement with previous results (XHI ∼ 0.5 − 0.9).
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".