A Holistic Perspective on the Dynamics of G035.39-00.33: The Interplay between Gas and Magnetic Fields
Bibliographic record
Abstract
Abstract Magnetic field plays a crucial role in shaping molecular clouds and regulating star formation, yet the complete information on the magnetic field is not well constrained owing to the limitations in observations. We study the magnetic field in the massive infrared dark cloud G035.39-00.33 from dust continuum polarization observations at 850 μm with SCUBA-2/POL-2 at JCMT for the first time. The magnetic field tends to be perpendicular to the densest part of the main filament (F M), whereas it has a less defined relative orientation in the rest of the structure, where it tends to be parallel to some diffuse regions. A mean plane-of-the-sky magnetic field strength of ∼50 μG for F M is obtained using the Davis–Chandrasekhar–Fermi method. Based on 13CO (1–0) line observations, we suggest a formation scenario of F M due to large-scale (∼10 pc) cloud–cloud collision. Using additional NH3 line data, we estimate that F M will be gravitationally unstable if it is only supported by thermal pressure and turbulence. The northern part of F M, however, can be stabilized by a modest additional support from the local magnetic field. The middle and southern parts of F M are likely unstable even if the magnetic field support is taken into account. We claim that the clumps in F M may be supported by turbulence and magnetic fields against gravitational collapse. Finally, we identified for the first time a massive (∼200 M ⊙), collapsing starless clump candidate, “c8,” in G035.39-00.33. The magnetic field surrounding “c8” is likely pinched, hinting at an accretion flow along the filament.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".