Spectral index of the Galactic foreground emission in the 50–87 MHz range
Bibliographic record
Abstract
ABSTRACT Total-power radiometry with individual meter-wave antennas is a potentially effective way to study the Cosmic Dawn (z ∼ 20) through measurement of the sky brightness arising from the 21 cm transition of neutral hydrogen, provided this can be disentangled from much stronger Galactic and extra-galactic foregrounds. In the process, measured spectra of integrated sky brightness temperature can be used to quantify the foreground emission properties. In this work, we analyse a subset of data from the Large-aperture Experiment to Detect the Dark Age (LEDA) in the 50–87 MHz range and constrain the foreground spectral index β in the northern sky visible from mid-latitudes. We focus on two zenith-directed LEDA radiometers and study how estimates of β vary with local sidereal time (LST). We correct for the effect of gain pattern chromaticity and compare estimated absolute temperatures with simulations. We select a reference data set consisting of 14 d of observations in optimal conditions. Using this data set, we find, for one radiometer, that β varies from −2.55 at LST <6 h to a steeper −2.58 at LST ∼13 h, consistently with sky models and previous southern sky measurements. In the 13 − 24 h LST range, however, we find that β varies between −2.55 and −2.61 (data scatter ∼0.01). We observe a similar β versus LST trend for the second radiometer, although with slightly smaller |β| over the 24 h, in the −2.46 < β < −2.43 range (data scatter ∼ 0.02). Combining all data gathered during the extended campaign between mid-2018 and mid-2019, and focusing on the LST = 9−12.5 h range, we infer good instrument stability and find −2.56 < β < −2.50 with 0.09 < Δβ < 0.12.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".