Grain Growth in the Dust Ring with a Crescent around the Very Low-mass Star ZZ Tau IRS with JVLA
Bibliographic record
Abstract
Abstract The azimuthal asymmetries of dust rings in protoplanetary disks such as a crescent around young stars are often interpreted as dust traps, and thus as ideal locations for planetesimal and planet formations. Whether such dust traps effectively promote planetesimal formation in disks around very low-mass stars (VLM; a mass of ≲0.2 M ☉) is debatable, as the dynamical and grain growth timescales in such systems are long. To investigate grain growth in such systems, we studied the dust ring with a crescent around the VLM star ZZ Tau IRS using the Karl G. Jansky Very Large Array at centimeter wavelengths. Significant signals were detected around ZZ Tau IRS. To estimate the maximum grain size ( a max ) in the crescent, we compared the observed spectral energy distribution (SED) with SEDs for various a max values predicted by radiative transfer calculations. We found a max ≳ 1 mm and ≲60 μm in the crescent and ring, respectively, though our modeling efforts rely on uncertain dust properties. Our results suggest that grain growth occurred in the ZZ Tau IRS disk, relative to the sub-micron-sized interstellar medium. Planet formation in a crescent with millimeter-sized pebbles might proceed more efficiently than in other regions with submillimeter-sized pebbles via pebble accretion scenarios.
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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 | 0.000 | 0.000 |
| 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".