90 GHz AND 150 GHz OBSERVATIONS OF THE ORION M42 REGION. A SUBMILLIMETER TO RADIO ANALYSIS
Bibliographic record
Abstract
We have used the new 90 GHz MUSTANG camera on the Robert C. Byrd Green Bank Telescope (GBT) to map the bright Huygens region of the star-forming region M42 with a resolution of 9'' and a sensitivity of 2.8 mJy beam −1 . Ninety GHz is an interesting transition frequency, as MUSTANG detects both the free–free emission characteristic of the H ii region created by the Trapezium stars, normally seen at lower frequencies, and thermal dust emission from the background OMC1 molecular cloud, normally mapped at higher frequencies. We also present similar data from the 150 GHz GISMO camera taken on the IRAM 30 m telescope. This map has 15'' resolution. By combining the MUSTANG data with 1.4, 8, and 21 GHz radio data from the VLA and GBT, we derive a new estimate of the emission measure averaged electron temperature of T e = 11376 ± 1050 K by an original method relating free–free emission intensities at optically thin and optically thick frequencies. Combining Infrared Space Observatory –long wavelength spectrometer ( ISO –LWS) data with our data, we derive a new estimate of the dust temperature and spectral emissivity index within the 80'' ISO –LWS beam toward Orion KL/BN, T d = 42 ± 3 K and β d = 1.3 ± 0.1. We show that both T d and β d decrease when going from the H ii region and excited OMC1 interface to the denser UV shielded part of OMC1 (Orion KL/BN, Orion S). With a model consisting of only free–free and thermal dust emission, we are able to fit data taken at frequencies from 1.5 GHz to 854 GHz (350 μm).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".