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The Investigation of Orbit-Stabilizer Theorem and Its Applications

2025· article· en· W4415181922 on OpenAlexaff
Yuming Li

Bibliographic record

VenueTheoretical and Natural Science · 2025
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Control Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOrbit (dynamics)Lemma (botany)Stabilizer (aeronautics)Fundamental theoremBrouwer fixed-point theoremGroup (periodic table)Element (criminal law)Group theoryAction (physics)

Abstract

fetched live from OpenAlex

Group theory is an important area of modern mathematics, and the orbit-stabilizer theorem is a significant conclution in all of the group theory as it is the basic of many other conclusions. This article introduces theory of group action and the definition of orbit and stabilizer as a background for orbit stabilizer theorem. The theorem itself was then stated with proof. Orbit-stabilizer theorem says that when a finite group is acting on a finite set, the orbit of any element of the set must have the same size with number of left cosets of stabilizer of the element in the group. The proof was then given using the fact that two sets with a bijection between them must have same size. Examples of applications in the proof of Cauchy’s theorem and Burnside’s lemma were given to show the importance of orbit stabilizer theorem in Group theory. Orbit-stabilizer theorem is a central part in the proof of both of those results.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0020.005
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.002
GPT teacher head0.192
Teacher spread0.190 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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