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Record W4238400500 · doi:10.1017/cbo9781107340985.003

Introduction

2003· book-chapter· en· W4238400500 on OpenAlexaff
Walter Tholen

Bibliographic record

VenueCambridge University Press eBooks · 2003
Typebook-chapter
Languageen
FieldMathematics
TopicHistory and Theory of Mathematics
Canadian institutionsYork University
Fundersnot available
KeywordsNoether's theoremHausdorff spaceAbstract algebraKey (lock)PerceptionAlgebra over a fieldMathematicsComputer sciencePure mathematicsMathematics educationEpistemologyPhilosophyComputer security

Abstract

fetched live from OpenAlex

Following the many splendid mathematical discoveries of the nineteenth century, mathematicians like Felix Hausdorff and Emmy Noether formalized the key-notions and thereby the categories which enable us to pursue modern structural mathematics. Bourbaki's monumental work gives the most comprehensive testimony of this rapid development during the first half of the twentieth century. Despite the laudable trend toward emphasizing applications, for the past few decades there has been little change in the overall perception of which general notions are to be considered important, and they continue to dominate the standard courses on topology and algebra. Soon after Samuel Eilenberg and Saunders Mac Lane coined the notions of category, functor and natural transformation in the 1940s, a very different way of doing structural mathematics emerged which was promoted especially in homo-logical algebra. Rather than building objects made up from sets with a structure, like topological spaces and modules over a ring, one imposes additional conditions on a category which make its objects behave like the structured sets one has in mind. Hence, rather than relying on a set-theoretic foundation on which to build the structures at issue, one moves into a “fully equipped building” in which to explore the objects of interest. Indeed, the category theory of the 1950s, especially Alexander Grothendieck's work, showed that a great deal of module theory can be performed in any abelian category and which abelian categories are actually-equivalent to module categories.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.710
Threshold uncertainty score0.969

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2900.152

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 head0.034
GPT teacher head0.213
Teacher spread0.179 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2003
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicHistory and Theory of MathematicsFrench-language works237,207