MAGNETIC FIELD STRUCTURES AND TURBULENT COMPONENTS IN THE STAR-FORMING MOLECULAR CLOUDS OMC-2 AND OMC-3
Bibliographic record
Abstract
The SCUBA polarized 850 μm thermal emission data of the OMC-2 region in Orion A are added to and homogeneously reduced with data already available in the OMC-3 region. The data set shows that OMC-2 is a region generally less polarized than OMC-3. Where coincident, most of the 850 μm polarization pattern is similar to that measured in 350 μm polarization data. Only 850 μm polarimetry data have been obtained in and around MMS7, FIR1 and FIR2, and in the region south of FIR6. A realignment of the polarization vectors with the filament can be seen near FIR1 in the region south of OMC-3. An analysis shows that the energy injected by CO outflows and H 2 jets associated with OMC-2 and OMC-3 does not appear to alter the polarization patterns at a scale of the 14'' resolution beam. A second-order structure function analysis of the polarization position angles shows that OMC-2 is a more turbulent region than OMC-3. OMC-3 appears to be a clear case of a magnetically dominated region with respect to the turbulence. However, for OMC-2 it is not clear that this is the case. A more in-depth analysis of five regions displayed along OMC-2/3 indicates a decrease of the mean polarization degree and an increase of the turbulent angular dispersion from north to south. A statistical analysis suggests the presence of two depolarization regimes in our maps: one regime including the effects of the cores, the other one excluding it.
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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) | 0.000 | 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".