Dust emissivity in the star-forming filament OMC 2/3
Bibliographic record
Abstract
We present new measurements of the dust emissivity index, β, for the high-mass, star-forming OMC 2/3 filament. We combined 160−500 μm data from Herschel with long-wavelength observations at 2 mm and fit the spectral energy distributions across a ≃2 pc long, continuous section of OMC 2/3 at 15 000 AU (0.08 pc) resolution. With these data, we measured β and reconstructed simultaneously the filtered-out large-scale emission at 2 mm. We implemented both variable and fixed values of β, finding that β = 1.7−1.8 provides the best fit across most of OMC 2/3. These β values are consistent with a similar analysis carried out with filtered Herschel data. Thus, we show that β values derived from spatial filtered emission maps agree well with those values from unfiltered data at the same resolution. Our results contradict the very low β values (~0.9) previously measured in OMC 2/3 between 1.2 mm and 3.3 mm data, which we attribute to elevated fluxes in the 3.3 mm observations. Therefore, we find no evidence of rapid, extensive dust grain growth in OMC 2/3. Future studies with Herschel data and complementary ground-based long-wavelength data can apply our technique to obtain reliable determinations of β in nearby cold molecular clouds.
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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 | 0.000 |
| 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".