Bibliographic record
Abstract
The star β Pictoris hosts the best studied circumstellar disk to date. Nonetheless, a long-standing puzzle has been around since the detection of metallic gas in the disk: radiation pressure from the star should blow the gas away, yet the observed motion is consistent with Keplerian rotation. In this work we search for braking mechanisms that can resolve this discrepancy. We find that all species affected by radiation force are largely ionized and dynamically coupled into a single fluid by Coulomb collisions, reducing the radiation force on species feeling the strongest acceleration. For a gas of solar composition, the effective radiation force still exceeds gravity, while a gas of enhanced carbon abundance could be self-braking. We also explore two other braking agents: collisions with dust grains and neutral gas. Grains surrounding β Pic are photoelectrically charged to a positive electrostatic potential. If a significant fraction of the grains are carbonaceous (10% in the midplane and larger at higher altitudes), ions can be slowed down to satisfy the observed velocity constraints. For neutral gas to brake the ion fluid, we find a minimum required mass ≈0.03 M ⊕ , consistent with observed upper limits on the hydrogen column density and substantially reduced relative to previous estimates. Our results favor a scenario in which metallic gas is generated by grain evaporation in the disk, perhaps during grain-grain collisions. We exclude a primordial origin for the gas but cannot rule out its production by falling evaporating bodies near the star.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".