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Record W4405812762 · doi:10.37236/12464

The Lexicographically Least Binary Rich Word Achieving the Repetition Threshold

2024· article· en· W4405812762 on OpenAlexafffund
James D. Currie, Narad Rampersad

Bibliographic record

VenueThe Electronic Journal of Combinatorics · 2024
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsUniversity of Winnipeg
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLexicographical orderRepetition (rhetorical device)Binary numberWord (group theory)ArithmeticMathematicsComputer scienceCombinatoricsLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

A word is rich if each of its length $n$ factors contains $n$ distinct non-empty palindromes. For a language ${\mathcal L}$, the repetition threshold of ${\mathcal L}$ is defined by$$\text{RT}({\mathcal L})=\sup\{k: \text{ every infinite word of ${\mathcal L}$ contains a $k$-power}\}.$$Currie et al. (2020) proved that the repetition threshold for binary rich words is $2+\sqrt{2}/2$. We exhibit the lexicographically least infinite binary rich word attaining this threshold.

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)0.004
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.000
Research integrity0.0000.002
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 head0.006
GPT teacher head0.248
Teacher spread0.242 · 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.

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

Citations2
Published2024
Admission routes2
Has abstractyes

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