Combined effects of disc winds and turbulence-driven accretion on planet populations
Bibliographic record
Abstract
ABSTRACT Recent surveys show that protoplanetary discs have lower levels of turbulence than expected based on their observed accretion rates. A viable solution to this is that magnetized disc winds dominate angular momentum transport. This has several important implications for planet formation processes. We compute the physical and chemical evolution of discs and the formation and migration of planets under the combined effects of angular momentum transport by turbulent viscosity and disc winds. We take into account the critical role of planet traps to limit Type I migration in all of these models and compute thousands of planet evolution tracks for single planets drawn from a distribution of initial disc properties and turbulence strengths. We do not consider multiplanet models nor include N-body planet–planet interactions. Within this physical framework we find that populations with a constant value disc turbulence and winds strength produce mass–semimajor axis distributions in the M–a diagram with insufficient scatter to compare reasonably with observations. However, populations produced as a consequence of sampling discs with a distribution of the relative strengths of disc turbulence and winds fit much better. Such models give rise to a substantial super Earth population at orbital radii 0.03–2 au, as well as a clear separation between the produced hot Jupiter and warm Jupiter populations. Additionally, this model results in a good comparison with the exoplanetary mass–radius distribution in the M–R diagram after post-disc atmospheric photoevaporation is accounted for.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".