The JCMT Gould Belt Survey: the effect of molecular contamination in SCUBA-2 observations of Orion A
Bibliographic record
Abstract
Thermal emission from cold dust grains in giant molecular clouds can be used to probe the physical properties, such as density, temperature and emissivity in star-forming regions. We present the Submillimetre Common-User Bolometer Array (SCUBA-2) shared-risk observations at 450 and 850 μm of the Orion A molecular cloud complex taken at the James Clerk Maxwell Telescope (JCMT). Previous studies showed that molecular emission lines can contribute significantly to the measured fluxes in those continuum bands. We use the Heterodyne Array Receiver Programme 12CO J = 3−2 integrated intensity map for Orion A in order to evaluate the molecular line contamination and its effects on the SCUBA-2 maps. With the corrected fluxes, we have obtained a new spectral index α map for the thermal emission of dust in the well-known integral-shaped filament. Furthermore, we compare a sample of 33 sources, selected over the Orion A molecular cloud complex for their high 12CO J = 3−2 line contamination, to 27 previously identified clumps in OMC 4. This allows us to quantify the effect of line contamination on the ratio of 850–450 μm flux densities and how it modifies the deduced spectral index of emissivity β for the dust grains. We also show that at least one Spitzer-identified protostellar core in OMC 5 has a 12CO J = 3−2 contamination level of 16 per cent. Furthermore, we find the strongest contamination level (44 per cent) towards a young star with disc near OMC 2. This work is part of the JCMT Gould Belt Legacy Survey.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".