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Record W1967415065 · doi:10.1142/s0129054112400709

BOUNDED PARIKH AUTOMATA

2012· article· en· W1967415065 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Foundations of Computer Science · 2012
Typearticle
Languageen
FieldComputer Science
Topicsemigroups and automata theory
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBounded functionClass (philosophy)AutomatonSet (abstract data type)Discrete mathematicsAffine transformationMathematicsWord (group theory)Regular languagePure mathematicsComputer scienceTheoretical computer scienceProgramming languageArtificial intelligenceMathematical analysis

Abstract

fetched live from OpenAlex

The Parikh finite word automaton model (PA) was introduced and studied by Klaedtke and Rueß. Here, we present some expressiveness properties of a restriction of the deterministic affine PA recently introduced, and use them as a tool to show that the bounded languages recognized by PA are the same as those recognized by deterministic PA. Moreover, this class of languages is shown equal to the class of bounded languages with a semilinear iteration set.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.646
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.005
Open science0.0040.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.306
Teacher spread0.288 · 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