Continuum sources from the THOR survey between 1 and 2 GHz
Bibliographic record
Abstract
We carried out a large program with the Karl G. Jansky Very Large Array (VLA): “THOR: The H i, OH, Recombination line survey of the Milky Way”. We observed a significant portion (~100 deg2) of the Galactic plane in the first quadrant of the Milky Way in the 21 cm H i line, 4 OH transitions, 19 radio recombination lines, and continuum from 1 to 2 GHz. In this paper we present a catalog of the continuum sources in the first half of the survey (l = 14.0−37.9° and l = 47.1−51.2°, | b | ≤ 1.1°) at a spatial resolution of 10−25″, depending on the frequency and sky position with a spatially varying noise level of ~0.3−1 mJy beam-1. The catalog contains ~4400 sources. Around 1200 of these are spatially resolved, and ~1000 are possible artifacts, given their low signal-to-noise ratios. Since the spatial distribution of the unresolved objects is evenly distributed and not confined to the Galactic plane, most of them are extragalactic. Thanks to the broad bandwidth of the observations from 1 to 2 GHz, we are able to determine a reliable spectral index for ~1800 sources. The spectral index distribution reveals a double-peaked profile with maxima at spectral indices of α ≈ −1 and α ≈ 0, corresponding to steep declining and flat spectra, respectively. This allows us to distinguish between thermal and non-thermal emission, which can be used to determine the nature of each source. We examine the spectral index of ~300 known H ii regions, for which we find thermal emission with spectral indices around α ≈ 0. In contrast, supernova remnants (SNR) show non-thermal emission with α ≈ −0.5 and extragalactic objects generally have a steeper spectral index of α ≈ −1. Using the spectral index information of the THOR survey, we investigate potential SNR candidates. We classify the radiation of four SNR candidates as non-thermal, and for the first time, we provide strong evidence for the SNR origin of these candidates.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".