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Understanding the Spins of Young Stars

2007· preprint· en· W1488807697 on OpenAlexaff
Sean P. Matt, Ralph E. Pudritz

Bibliographic record

VenuearXiv (Cornell University) · 2007
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhysicsAngular momentumAstrophysicsStarsAccretion (finance)AstronomySpin (aerodynamics)Circumstellar diskStellar windStellar rotationAccretion discSpinsClassical mechanics

Abstract

fetched live from OpenAlex

We review the theoretical efforts to understand why pre-main-sequence stars spin much more slowly than expected. The first idea put forward was that massive stellar winds may remove substantial angular momentum. Since then, it has become clear that the magnetic interaction between the stars and their accretion disks explains many of the observed emission properties. The disk locking scenario, which assumes the magnetic star-disk interaction also solves the stellar spin problem, has received the most attention in the literature to date. However, recent considerations suggest that the torques in the star-disk interaction are insufficient for disk locking to explain the slow rotators. This prompts us to revisit stellar winds, and we conclude that stellar winds, working in conjunction with magnetospheric accretion, are a promising candidate for solving the angular momentum problem. We suggest future directions for both observations and theory, to help shed light on this issue.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.148
GPT teacher head0.189
Teacher spread0.041 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2007
Admission routes1
Has abstractyes

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