Herschel-ATLAS: the far-infrared-radio correlation at z < 0.5★
Bibliographic record
Abstract
We use data from the Herschel-ATLAS to investigate the evolution of the far-infrared–radio correlation over the redshift range 0 < z < 0.5. Using the total far-infrared luminosity of all >5σ sources in the Herschel-ATLAS Science Demonstration Field and cross-matching these data with radio data from the Faint Images of the Radio Sky at Twenty-Centimetres (FIRST) survey and the NRAO Very Large Array (VLA) Northern Sky Survey (NVSS), we obtain 104 radio counterparts to the Herschel sources. With these data we find no evidence for evolution in the far-infrared–radio correlation over the redshift range 0 < z < 0.5, where the median value for the ratio between far-infrared and radio luminosity, qIR, over this range is qIR= 2.40 ± 0.12 (and a mean of qIR= 2.52 ± 0.03 accounting for the lower limits), consistent with both the local value determined from IRAS and values derived from surveys targeting the high-redshift Universe. By comparing the radio fluxes of our sample measured from both FIRST and NVSS we show that previous results suggesting an increase in the value of qIR from high to low redshift may be the result of resolving out extended emission of the low-redshift sources with relatively high-resolution interferometric data, although contamination from active galactic nuclei could still play a significant role. We also find tentative evidence that the longer wavelength cooler dust is heated by an evolved stellar population which does not trace the star formation rate as closely as the shorter wavelength ≲ 250 μm emission or the radio emission, supporting suggestions based on detailed models of individual galaxies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.021 |
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".