The GBT Diffuse Ionized Gas Survey (GDIGS): Survey Overview and First Data Release
Bibliographic record
Abstract
Abstract The Green Bank Telescope (GBT) Diffuse Ionized Gas Survey (GDIGS) traces ionized gas in the Galactic midplane by measuring 4–8 GHz radio recombination line (RRL) emission. The nominal survey zone is 32.°3 > ℓ > − 5°, ∣b∣ < 0.°5, but coverage extends above and below the plane in select fields and additionally includes the areas around W47 (ℓ ≃ 37.°5) and W49 (ℓ ≃ 43°). GDIGS simultaneously observes 22 Hnα (15 usable), 25 Hnβ (18 usable), and 8 Hnγ RRLs (all usable), as well as multiple molecular line transitions (including those of , H2CO, and CH3OH). Here, we describe the GDIGS survey parameters and characterize the RRL data, focusing primarily on the Hnα data. We produce sensitive data cubes by averaging the usable RRLs, after first smoothing to a common spectral resolution of 0.5 km s−1 and a spatial resolution of 2.′65 for Hnα, 2.′62 for Hnβ, and 2.′09 for Hnγ. The average spectral noise per spaxel in the Hnα data cubes is ∼10 mK (∼5 mJy beam−1). This sensitivity allows GDIGS to detect RRLs from plasma throughout the inner Galaxy. The GDIGS Hnα data are sensitive to emission measures EM ≳ 1100 cm−6 pc, which corresponds to a mean electron density 〈n e 〉 ≳ 30 cm−3 for a 1 pc path length or 〈n e 〉 ≳ 1 cm−3 for a 1 kpc path length.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.015 |
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".