Near-infrared imaging polarimetry toward M 17 SWex
Bibliographic record
Abstract
Abstract We conducted near-infrared ($\mathit {JHK}_{\rm s}$) imaging polarimetry toward the infrared dark cloud (IRDC) M 17 SWex, including almost all of the IRDC filaments as well as its outskirts, with the polarimeter SIRPOL on the IRSF 1.4 m telescope. We revealed the magnetic fields of M 17 SWex with our polarization-detected sources that were selected by some criteria based on their near-IR colors and the column densities toward them, which were derived from the Herschel data. The selected sources indicate not only that the ordered magnetic field is perpendicular to the cloud elongation as a whole, but also that at both ends of the elongated cloud the magnetic field appears to be bent toward its central part, i.e., a large-scale hourglass-shaped magnetic field perpendicular to the cloud elongation. In addition to this general trend, the elongations of the filamentary subregions within the dense parts of the cloud appear to be mostly perpendicular to their local magnetic fields, while the magnetic fields of the outskirts appear to follow the thin filaments that protrude from the dense parts. The magnetic strengths were estimated to be ∼70–$300\, \mu$G in the subregions, of which the lengths and average number densities are ∼3–9 pc and ∼2–7 × 103 cm−3, respectively, by the Davis–Chandrasekhar–Fermi method with the angular dispersion of our polarization data and the velocity dispersion derived from the C18O (J = 1–0) data obtained by the Nobeyama 45 m telescope. These field configurations and our magnetic stability analysis of the subregions imply that the magnetic field has controlled the formation/evolution of the M 17 SWex cloud.
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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 | 0.001 |
| 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".