Magnetic Fields in Massive Star-forming Regions (MagMaR). II. Tomography through Dust and Molecular Line Polarization in NGC 6334I(N)
Bibliographic record
Abstract
Abstract Here, we report ALMA detections of polarized emission from dust, CS( J = 5 → 4), and C 33 S( J = 5 → 4) toward the high-mass star-forming region NGC 6334I(N). A clear “hourglass” magnetic field morphology was inferred from the polarized dust emission, which is also directly seen from the polarized CS emission across velocity, where the polarization appears to be parallel to the field. By considering previous findings, the field retains a pinched shape that can be traced to clump length scales from the envelope scales traced by ALMA, suggesting that the field is dynamically important across multiple length scales in this region. The CS total intensity emission is found to be optically thick ( τ CS = 32 ± 12) while the C 33 S emission appears to be optically thin ( τ C 33 S = 0.1 ± 0.01 ). This suggests that sources of anisotropy other than large velocity gradients, i.e., anisotropies in the radiation field, are required to explain the polarized emission from CS seen by ALMA. By using four variants of the Davis–Chandrasekhar–Fermi technique and the angle dispersion function methods (ADF), we obtain an average of the estimates for the magnetic field strength on the plane of the sky of B pos = 16 mG from the dust and B pos ∼ 2 mG from the CS emission, where each emission traces different molecular hydrogen number densities. This effectively enables a tomographic view of the magnetic field within a single ALMA observation.
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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 | 0.000 |
| 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".