eDIG-CHANGES I: extended Hα emission from the extraplanar diffuse ionized gas (eDIG) around CHANG-ES galaxies
Bibliographic record
Abstract
ABSTRACT The extraplanar diffuse ionized gas (eDIG) represents the cool/warm ionized gas reservoir around galaxies. We present spatial analysis of the Hα images of 22 nearby edge-on spiral galaxies taken with the Apache Point Observatory 3.5-m telescope (eDIG-CHANGES). We conduct an exponential fit to the vertical Hα intensity profiles of the galaxies, of which 16 can be decomposed into thin + thick disk components. The median value of the Hα scale height of the thick disk is $\langle h_{\rm H\alpha }\rangle =1.13\pm 0.14\rm ~kpc$. We further examine the dependence of hHα on the stellar mass, SFR, and SFR surface density (SFRSD) of the galaxies. We find a tight sublinear correlation between hHα and SFR, expressed in hHα ∝ SFRα, where α ≈ 0.29. Moreover, the offset of individual galaxies from the best-fit SFR-hHα relation, expressed in hHα/SFRα, shows significant anti-correlation with SFRSD. We further compare the vertical extension of the eDIG to multi-wavelength measurements of other CGM phases. We find the eDIG slightly more extended than the neutral gas. This indicates the existence of some extended ionizing sources, in addition to the leaking photons from the disk star formation regions. Most galaxies have an X-ray scale height smaller than Hα, suggesting the majority of the X-ray photons are actually from the thick disk instead of the extended CGM. hHα is comparable to the L-band radio continuum scale height. This indicates that the thermal and non-thermal electrons have similar spatial distributions, a natural result if both are transported outwards by a galactic wind. This further indicates the thermal gas, cosmic rays, and magnetic field may be close to energy equipartition.
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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 | 0.000 |
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".