CHANG-ES XXXI—A Decade of CHANG-ES: What We Have Learned from Radio Observations of Edge-on Galaxies
Bibliographic record
Abstract
CHANG-ES (Continuum Halos in Nearby Galaxies—an EVLA Survey) is an ambitious project to target 35 nearby disk galaxies that are edge-on to the line of sight. The orientation permits both the disk and halo regions to be studied. The observations were initially at 1.5 GHz (L-band) and 6.0 GHz (C-band) in a variety of VLA array configurations, and in all four Stokes parameters, which allowed for spatially resolved images in total intensity plus polarization. The inclusion of polarization is unique to an edge-on galaxy survey and reveals the galaxies’ halo magnetic fields. This paper will summarize the results to date, some of which are new phenomena, never seen prior to CHANG-ES. For example, we see that ‘X-type’ fields, as well as rotation measure reversals, are common features of spiral galaxies. Further observations at 3.0 GHz (S-band) as well as future scientific opportunities will also be described.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| 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".