Formation and survivability of giant planets on wide orbits
Bibliographic record
Abstract
Motivated by the recent discovery of massive planets on wide orbits, we present a mechanism for the formation of such planets via disk fragmentation in the embedded phase of star formation. In this phase, the forming disk intensively accretes matter from the natal cloud core and undergoes several fragmentation episodes. However, most fragments are either destroyed or driven into the innermost regions (and probably onto the star) due to angular momentum exchange with spiral arms, leading to multiple FU-Ori-like bursts and disk expansion. Fragments that are sufficiently massive and form in the late embedded phase (when the disk conditions are less extreme) may open a gap and evolve into giant planets on typical orbits of several tens to several hundreds of AU. For this mechanism to work, the natal cloud core must have sufficient mass and angular momentum to trigger the burst mode and also form extended disks of the order of several hundreds of AU. When mass loading from the natal cloud core diminishes and the main fragmentation phase ends, such extended disks undergo a transient episode of contraction and density increase, during which they may give birth to a last and survivable set of giant planets on wide and relatively stable orbits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".