JCMT BISTRO Survey: Magnetic Fields within the Hub-filament Structure in IC 5146
Bibliographic record
Abstract
Abstract We present the 850 μm polarization observations toward the IC 5146 filamentary cloud taken using the Submillimetre Common-User Bolometer Array 2 (SCUBA-2) and its associated polarimeter (POL-2), mounted on the James Clerk Maxwell Telescope, as part of the B-fields In STar forming Regions Observations. This work is aimed at revealing the magnetic field morphology within a core-scale (≲1.0 pc) hub-filament structure (HFS) located at the end of a parsec-scale filament. To investigate whether the observed polarization traces the magnetic field in the HFS, we analyze the dependence between the observed polarization fraction and total intensity using a Bayesian approach with the polarization fraction described by the Rice likelihood function, which can correctly describe the probability density function of the observed polarization fraction for low signal-to-noise ratio data. We find a power-law dependence between the polarization fraction and total intensity with an index of 0.56 in A V ∼ 20–300 mag regions, suggesting that the dust grains in these dense regions can still be aligned with magnetic fields in the IC 5146 regions. Our polarization maps reveal a curved magnetic field, possibly dragged by the contraction along the parsec-scale filament. We further obtain a magnetic field strength of 0.5 ± 0.2 mG toward the central hub using the Davis–Chandrasekhar–Fermi method, corresponding to a mass-to-flux criticality of ∼1.3 ± 0.4 and an Alfvénic Mach number of <0.6. These results suggest that gravity and magnetic field are currently of comparable importance in the HFS and that turbulence is less important.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".