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Record W6989104286

Algebraic Processors

2007· dissertation· en· W6989104286 on OpenAlexaff

Bibliographic record

VenueMacSphere (McMaster University) · 2007
Typedissertation
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCorrectnessAlgebraic numberAlgebraic operationEquivalence (formal languages)Algebraic expressionAlgebra over a fieldAlgebraic theoryTask (project management)
DOInot available

Abstract

fetched live from OpenAlex

Algebraic simplification is the task of reducing an algebraic expression to a simpler form without changing the meaning of the expression. Simplification is generally a difficult task and may have different meanings according to what the subject considers as "simple" . This thesis starts off by reverse-engineering the concept of algebraic processors in the IMPS interactive mathematical proof system - which is responsible for handling all the algebraic simplification tasks - and discusses its algorithm and usage in detail. Then it explores the idea of algebraic processors as generic programs that can be configured for any type of algebraic structure to simplify expressions of that type by first formalizing the theory of algebraic processors of IMPS and then extending it to provide solutions for related topics. Algebraic processors can be defined for any user-defined algebra, as long as it conforms to the structure defined in this paper. The processors are defined as external units that can communicate with other mechanized mathematics systems in a trustable fashion and provide a program and a proof of correctness for any requests of simplification. Finally, some related processors such as one for simplification in partial orders and equivalence classes are outlined with some discussion of possible future expansions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.015
GPT teacher head0.225
Teacher spread0.211 · 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 teacher head, 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
Published2007
Admission routes1
Has abstractyes

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