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Record W2031779562 · doi:10.1142/s0218196710005686

WEAKLY ITERATED BLOCK PRODUCTS AND APPLICATIONS TO LOGIC AND COMPLEXITY

2010· article· en· W2031779562 on OpenAlexafffund
Howard Straubing, Pascal Tesson, Denis Thérien

Bibliographic record

VenueInternational Journal of Algebra and Computation · 2010
Typearticle
Languageen
FieldComputer Science
Topicsemigroups and automata theory
Canadian institutionsMcGill UniversityUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesAlexander von Humboldt-Stiftung
KeywordsMathematicsOperandIterated functionBracketing (phenomenology)Product (mathematics)Block (permutation group theory)Wreath productDiscrete mathematicsOrder (exchange)Bounded functionArithmeticCombinatorics

Abstract

fetched live from OpenAlex

Unlike the wreath product, the block product is not associative at the level of varieties. All decomposition theorems involving block products, such as the bilateral version of Krohn–Rhodes' theorem, have always assumed a right-to-left bracketing of the operands. We consider here the left-to-right bracketing, which is generally weaker. More precisely, we are interested in characterizing for any pseudovarieties of monoids U, V the smallest pseudovariety W that contains U and such that W □ V = W. This allows us to obtain new decomposition results for a number of important varieties such as DA, DO and DA * G. We apply these results to characterize the regular languages definable with generalized first-order sentences using only two variables and to shed new light on recent results on regular languages recognized by bounded-depth circuits with a linear number of wires and regular languages with small communication complexity.

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)0.003
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 score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.283
Teacher spread0.263 · 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

Citations3
Published2010
Admission routes2
Has abstractyes

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Same venueInternational Journal of Algebra and ComputationSame topicsemigroups and automata theoryFrench-language works237,207