Spectral index of the diffuse radio background between 50 and 100 MHz
Bibliographic record
Abstract
We report the spectral index of diffuse radio emission between 50 and 100 MHz from data collected with two implementations of the Experiment to Detect the Global EoR Signature (EDGES) low-band system. EDGES employs a wide-beam zenith-pointing dipole antenna centred on a declination of −26.7°. We measure the sky brightness temperature as a function of frequency averaged over the EDGES beam from 244 nights of data acquired between 2016 September 14 and 2017 August 27. We derive the spectral index, β, as a function of local sidereal time (LST) using night-time data and a two-parameter fitting equation. We find −2.59 < β < −2.54 ± 0.011 between 0 and 12 h LST, ignoring ionospheric effects. When the Galactic Centre is in the sky, the spectral index flattens, reaching β = −2.46 ± 0.011 at 18.2 h. The measurements are stable throughout the observations with night-to-night reproducibility of σβ < 0.004 except for the LST range of 7 to 12 h. We compare our measurements with predictions from various global sky models and find that the closest match is with the spectral index derived from the Guzmán and Haslam sky maps, similar to the results found with the EDGES high-band instrument for 90–190 MHz. Three-parameter fitting was also evaluated with the result that the spectral index becomes more negative by ∼0.02 and has a maximum total uncertainty of 0.016. We also find that the third parameter, the spectral index curvature, γ, is constrained to −0.11 < γ < −0.04. Correcting for expected levels of night-time ionospheric absorption causes β to become more negative by 0.008–0.016 depending on LST.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".