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Record W2240830268

Algunos aspectos del álgebra no asociativa

2014· article· es· W2240830268 on OpenAlexaff
María del Pilar Benito Clavijo, Jesús Antonio Laliena Clemente, Sara Madariaga Merino, José María Pérez Izquierdo, Daniel de la Concepción

Bibliographic record

VenueZubía · 2014
Typearticle
Languagees
FieldMathematics
TopicAdvanced Topics in Algebra
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsHumanitiesLie algebraNothingAlgebra over a fieldPure mathematicsMathematicsPhilosophyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

espanolUna gran cantidad de estructuras algebraicas, y entre las mas significativas las algebras asociativas y de Jordan, estan fuertemente vinculadas a las algebras de Lie y tambien a interesantes geometrias. Estas relaciones dan explicacion a determinadas excepcionalidades en algebra y geometria que no son sino manifestaciones de los mismos fenomenos. En esta resena se analiza una parte de la actividad investigadora que el grupo de algebra de la Universidad de La Rioja ha realizado en los ultimos anos. Esta actividad se centra en el estudio de estructuras no asociativas que estan en el entorno de las algebras de Lie. EnglishA large number of algebraic structures, among which the associative and the Jordan algebras deserve special mention, are closely related to the Lie algebras and to some interesting geometries. These relationships explain certain exceptional behaviors in Algebra and Geometry, which are nothing but manifestations of the same phenomena. In this note we analyse part of the research made during the last years by the research group of Algebra of the University of La Rioja. This research focuses on the study of nonassociative structures related to Lie algebras.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.297
Teacher spread0.277 · 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
Published2014
Admission routes1
Has abstractyes

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