The multiplicity of 250-μm<i>Herschel</i>sources in the COSMOS field
Bibliographic record
Abstract
We investigate the multiplicity of extragalactic sources detected by the Herschel Space Observatory in the COSMOS field. Using 3.6- and 24-μm catalogues, in conjunction with 250-μm data from Herschel, we seek to determine if a significant fraction of Herschel sources are composed of multiple components emitting at 250 μm. We use the xid+ code, using Bayesian inference methods to produce probability distributions of the possible contributions to the observed 250-μm flux for each potential component. The fraction of Herschel flux assigned to the brightest component is highest for sources with total 250-μm fluxes <45 mJy; however, the flux in the brightest component is still highest in the brightest Herschel sources. The faintest 250-μm sources (30–45 mJy) have the majority of their flux assigned to a single bright component; the second brightest component is typically significantly weaker, and contains the remainder of the 250-μm source flux. At the highest 250-μm fluxes (45–110 mJy), the brightest and second brightest components are assigned roughly equal fluxes, and together are insufficient to reach 100 per cent of the 250-μm source flux. This indicates that additional components are required, beyond the brightest two components, to reproduce the observed flux. 95 per cent of the sources in our sample have a second component that contains more than 10 per cent of the total source flux. Particularly for the brightest Herschel sources, assigning the total flux to a single source may overestimate the flux contributed by around 150 per cent.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".