CLASSY. VIII. Exploring the Source of Ionization with UV Interstellar Medium Diagnostics in Local High-z Analogs*
Bibliographic record
Abstract
Abstract In the current JWST era, rest-frame UV spectra play a crucial role in enhancing our understanding of the interstellar medium (ISM) and stellar properties of the first galaxies in the epoch of reionization (z > 6). Here, we compare well-known and reliable optical diagrams sensitive to the main ionization source (i.e., star formation, SF; active galactic nuclei, AGN; and shocks) to UV counterparts proposed in the literature—the so-called “UV–BPT diagrams”—using the HST COS Legacy Archive Spectroscopic SurveY (CLASSY), which is the largest high-quality, high-resolution, and broad-wavelength range atlas of far-UV spectra for 45 local star-forming galaxies. In particular, we explore where CLASSY UV line ratios are located in the different UV diagnostic plots, taking into account state-of-the-art photoionization and shock models, and, for the first time, the measured ISM and stellar properties (e.g., gas-phase metallicity, ionization parameter, carbon abundance, and stellar age). We find that the combination of C iii] λ λ1907,9 He ii λ1640 and O iii] λ1666 can be a powerful tool to separate between SF, shocks, and AGN at subsolar metallicities. We also confirm that alternative diagrams without O iii] λ1666 still allow us to define an SF-locus, with some caveats. Diagrams including C iv λ λ1548,51 should be taken with caution given the complexity of this doublet profile. Finally, we present a discussion detailing the ISM conditions required to detect UV emission lines, visible only in low gas-phase metallicity (12 + log(O/H) ≲ 8.3) and high ionization parameter (log(U) ≳ −2.5) environments. Overall, CLASSY and our UV toolkit will be crucial in interpreting the spectra of the earliest galaxies that JWST is currently revealing.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".