Bibliographic record
Abstract
Most low-mass protostellar discs evolve in clustered environments where they are affected by external radiation fields, while others evolve in more isolated star-forming regions. Assuming that the magnetorotational instability (MRI) is the main source of viscosity, we calculate the size of a poorly ionized, MRI inactive and hence low viscosity region — the ‘dead zone’-in these protostellar discs. We include disc ionization by X-rays, cosmic rays, radioactive elements and thermal collisions, recombination by molecules, metals and grains, as well as the effect of turbulence stimulation in the dead zone by the active layers lying above it. We also calculate the gap-opening masses of planets, which are determined by a disc's viscosity and a disc aspect ratio, for discs in these environments and compare them with each other. We find that the dead zone is a robust feature of the protostellar discs that is largely independent of their environment, typically stretching out to ∼15 au. We analyse the possible effects of dead zones on planet formation, migration and eccentricity evolution. We show that the gap-opening mass inside the dead zone is expected to be of the order of terrestrial and ice giant mass planets while that outside the dead zone is Jovian or super-Jovian mass planets, largely independent of the star-forming environment. We show that dead zones can significantly slow down both type I and type II planetary migration due to their lower viscosity. We also find that the growth of eccentricity of massive extrasolar planets is particularly favourable through the planet-disc interaction inside the dead zones due to the large gaps expected to be opened by planets.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".