Comparison of Magnetic Field Structures on Different Scales in and around the Filamentary Dark Cloud GF 9
Bibliographic record
Abstract
New visible polarization data combined with existing IR and FIR polarization data are used to study how the magnetic field threading the filamentary molecular cloud GF 9 connects to larger structures in its general environment. When visible and NIR polarization data are combined, no evidence is found for a plateau in the polarization above extinction A V ≈ 1.3, as seen in dark clouds in Taurus. This lack of saturation effect suggests that even in the denser parts of GF 9 magnetic fields can be probed. The visible polarization is smooth and has a well-defined orientation. In the core region, the IR and FIR data are also well defined, but each with a different direction. A multiscale analysis of the magnetic field shows that on the scale of a few times the mean radial dimension of the molecular cloud, it is as if the magnetic field were "blind" to the spatial distribution of the filaments, while on smaller scales in the core region, multiwavelength polarimetry shows a rotation of the magnetic field lines in these denser phases. Finally, the Chandrasekhar and Fermi method is used to evaluate the magnetic field strength, indicating that the core region is approximately magnetically critical. A global interpretation suggests that in the core region an original poloidal field could have been twisted by a rotating elongated (core+envelope) structure. There is no evidence for turbulence, and ambipolar diffusion does not seem to be effective at the present time.
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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".