CHANG-ES. XVII. Hα Imaging of Nearby Edge-on Galaxies, New SFRs, and an Extreme Star Formation Region—Data Release 2
Bibliographic record
Abstract
Abstract We present new narrow-band Hα imaging for 24 nearby edge-on galaxies in the Continuum Halos in Nearby Galaxies—an EVLA Survey (CHANG-ES). We use the images in conjunction with the Wide-field Infrared Survey Explorer 22 μm imaging of the sample to estimate improved star formation rates (SFRs) using the updated recipe from Vargas et al. We explore correlations between the updated star formation properties and radio continuum scale heights, scale lengths, and diameters, measured in Krause et al. We find a newly discovered correlation between SFR and radio scale height that did not exist using mid-infrared (IR) only SFR calibrations. This implies that a mid-IR extinction correction should be applied to SFR calibrations when used in edge-on galaxies, due to attenuation by dust. The updated SFR values also show newly discovered correlations with radio scale length and radio diameter, implying that the previously measured relationship between radio scale height and radio diameter originates from star formation within the disk. We also identify a region of star formation located at extreme distance from the disk of NGC 4157, possibly ionized by a single O5.5 V star. This region is spatially coincident with an extended ultraviolet disk feature, as traced by the Galaxy Evolution Explorer near-ultraviolet imaging. We theorize that the star formation feature arose due to gravitational instability within gas from an accretion event. New Hα images from this work can be found at the CHANG-ES data release website, https://www.queensu.ca/changes .
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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 | 0.001 |
| 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) | 0.003 | 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".