THE RESPONSE OF GIANT STARS TO DYNAMICAL-TIMESCALE MASS LOSS
Bibliographic record
Abstract
We study the response of giant stars to mass loss. One-dimensional simulations of red and asymptotic giant branch stars with mass loss rates from 10 −3 up to a few M ☉ yr −1 show in no case any significant radius increase. The largest radius increase of 0.2% was found in the case with the lowest mass loss rate. For dynamical-timescale mass loss rates that may be encountered during a common envelope phase, the evolution is not adiabatic. The superadiabatic outer layer of the giant's envelope has a local thermal timescale comparable to the dynamical timescale. Therefore, this layer has enough time to readjust thermally. Moreover, the giant star is driven out of hydrostatic equilibrium and evolves dynamically. In these cases no increase of the stellar radius with respect to its initial value is found. If the mass loss rate is high enough, the superadiabaticity of the outer layer is lost progressively and a radiative zone forms due to a combination of thermal and dynamical readjustment. Conditions for unstable mass transfer based on adiabatic mass loss models that predict a significant radius increase may need to be re-evaluated.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".