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Record W3104517253

Homogeneous length functions on groups

2018· article· en· W3104517253 on OpenAlexaff
T. A. Fritz, Siddhartha Gadgil, Apoorva Khare, Pace P. Nielsen, Lior Silberman, Terence Tao

Bibliographic record

VenueNOT FOUND REPOSITORY (Indian Institute of Science Bangalore) · 2018
Typearticle
Languageen
FieldMathematics
TopicGeometric and Algebraic Topology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMathematicsHomogeneousCombinatoricsHomogeneity (statistics)Triangle inequalityBanach spaceHomogeneous functionSpace (punctuation)Mathematical analysis
DOInot available

Abstract

fetched live from OpenAlex

A pseudolength function defined on an arbitrary group G â� (G, ·, e, ( ) â��1 ) is a map â��: G â�� 0, +â��) obeying â��(e) â� 0, the symmetry property â��(x â��1 ) â� â��(x), and the triangle inequality â��(xy) â�¤ â��(x) + â��(y) for all x, y â�� G. We consider pseudolength functions which saturate the triangle inequality whenever x â� y, or equivalently those that are homogeneous in the sense that â��(x n ) â� nâ��(x) for all n â�� â��. We show that this implies that â��(x, y]) â� 0 for all x, y â�� G. This leads to a classification of such pseudolength functions as pullbacks from embeddings into a Banach space. We also obtain a quantitative version of our main result which allows for defects in the triangle inequality or the homogeneity property. © 2018, Mathematical Sciences Publishers. All rights reserved.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.004
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.033
GPT teacher head0.287
Teacher spread0.254 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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