The GBT Diffuse Ionized Gas Survey: Tracing the Diffuse Ionized Gas around the Giant Hii Region W43
Bibliographic record
Abstract
Abstract The Green Bank Telescope Diffuse Ionized Gas Survey (GDIGS) is a fully sampled radio recombination line (RRL) survey of the inner Galaxy at C-band (4–8 GHz). We average together ∼15 Hnα RRLs within the receiver bandpass to improve the spectral signal-to-noise ratio. The average beam size for the RRL observations at these frequencies is ∼2′. We grid these data to have spatial and velocity spacings of 30″ and 0.5 , respectively. Here we discuss the first RRL data from GDIGS: a 6 deg2 area surrounding the Galactic H II region complex W43. We attempt to create a map devoid of emission from discrete H II regions and detect RRL emission from the diffuse ionized gas (DIG) across nearly the entire mapped area. We estimate the intensity of the DIG emission by a simple empirical model, taking only the H II region locations, angular sizes, and RRL intensities into account. The DIG emission is predominantly found at two distinct velocities: ∼40 and ∼100 . While the 100 component is associated with W43 at a distance of ∼6 kpc, the origin of the 40 component is less clear. Since the distribution of the 40 emission cannot be adequately explained by ionizing sources at the same velocity, we hypothesize that the plasma at the two velocity components is interacting, placing the 40 DIG at a similar distance as the 100 emission. We find a correlation between dust temperature and integrated RRL intensity, suggesting that the same radiation field that heats the dust also maintains the ionization of the DIG.
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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 | 0.001 |
| 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".