Cm-wavelength observations of MWC 758: resolved dust trapping in a vortex
Bibliographic record
Abstract
The large crescents imaged by ALMA in transition discs suggest that azimuthal dust trapping concentrates the larger grains, but centimetre–wavelengths continuum observations are required to map the distribution of the largest observable grains. A previous detection at ∼1 cm of an unresolved clump along the outer ring of MWC 758 (Clump 1), and buried inside more extended sub-mm continuum, motivates followup VLA observations. Deep multiconfiguration integrations reveal the morphology of Clump 1 and additional cm-wave components that we characterize via comparison with a deconvolution of recent 342 GHz data (∼1 mm). Clump 1, which concentrates ∼1/3 of the whole disc flux density at ∼1 cm, is resolved as a narrow arc with a deprojected aspect ratio χ > 5.6, and with half the azimuthal width than at 342 GHz. The spectral trends in the morphology of Clump 1 are quantitatively consistent with the Lyra-Lin prescriptions for dust trapping in an anticyclonic vortex, provided with porous grains (f ∼ 0.2 ± 0.2) in a very elongated (χ ∼ 14 ± 3) and cold (|$T\sim 23\pm 2\,$|K) vortex. The same prescriptions constrain the turbulence parameter α and the gas surface density Σg through |$\log _{10}\left(\alpha \times \Sigma _g / \mathrm{g\, cm}^{-2} \right) \sim -2.3\pm 0.4$|, thus requiring values for Σg larger than a factor of a few compared to that reported in the literature from the CO isotopologues, if α ≲ 10−3. Such physical conditions imply an appreciably optically thick continuum even at cm-wavelengths (|$\tau _{33\, \mathrm{GHz}}\sim 0.2$|). A secondary and shallower peak at 342 GHz is about twice fainter relative to Clump 1 at 33 GHz. Clump 2 appears to be less efficient at trapping large grains.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".