Probing the turbulent ambipolar diffusion scale in molecular clouds with spectroscopy
Bibliographic record
Abstract
We estimate the turbulent ambipolar diffusion length-scale and magnetic field strength in the massive dense cores CygX-N03 and CygX-N53, located in the Cygnus-X star-forming region. The method we use requires comparing the velocity dispersions in the spectral line profiles of the coexistent ion and neutral pair H13CN and H13CO+ (J = 1 → 0) at different length-scales. We fit Kolmogorov-type power laws to the lower envelopes of the velocity dispersion spectra of the two species. This allows us to calculate the turbulent ambipolar diffusion scale, which in turn determines the plane-of-the-sky magnetic field strength. We find turbulent ambipolar diffusion length-scales of 3.8 ± 0.1 and 21.2 ± 0.4 mpc, and magnetic field strengths of 0.33 and 0.76 mG for CygX-N03 and CygX-N53, respectively. These magnetic field values have uncertainties of a factor of a few. Despite a lower signal-to-noise ratio of the data in CygX-N53 than in CygX-N03, and the caveat that its stronger field might stem in part from projection effects, the difference in field strengths suggests different fragmentation efficiencies of the two cores. Even though the quality of our data, obtained with the Institut de Radio Astronomie Millimetrique (IRAM) Plateau de Bure Interferometer, is somewhat inferior to previous single-dish data, we demonstrate that this method is suited also for observations at high spatial resolution.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".