Effects of Stellar Rotation in Parker's Hydrodynamic Stellar Wind Model.
Bibliographic record
Abstract
The effects of the stellar rotation and the consequent azimuthal stellar wind flow in Parker's [9] hydrodynamic stellar wind model are discussed. Of special interest is the emergence of a whole new hydrodynamic physics via a new critical point in the stellar wind flow, which supersedes the critical point in Parker's [9] hydrodynamic model. The effect of the stellar rotation is shown to cause the new critical point to occur lower in the corona, so the stellar wind experiences a stronger afterburner (as in an aircraft jet engine) action in the corona. For strong rotators, the new critical point is shown to occur at a fixed location for a given star, determined only by the basic stellar parameters like the mass M and the angular velocity, the variations in the stellar wind environment notwithstanding. The stellar rotation leads to stronger density fall-off and enhanced acceleration of the stellar wind at large distances from the star - this effect materializes even close to the star, for strong rotators. The stellar rotation causes the physical throat section of the effective de Laval nozzle associated with the stellar wind flow to become narrower, indicative of an enhanced flow acceleration. Thus, the stellar rotation leads to tenuous and faster stellar wind flows without change in the mass flux, and hence provides an efficient physical mechanism for protostars and strong rotators to lose their angular momentum quickly.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".