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Record W2803286074 · doi:10.1080/10236198.2018.1471471

On the solution space of the Golomb recursion

2018· article· en· W2803286074 on OpenAlexaff
Matthew Sunohara, Stephen M. Tanny

Bibliographic record

VenueThe Journal of Difference Equations and Applications · 2018
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGolomb codingMathematicsRecursion (computer science)ConjectureSequence (biology)Equivalence (formal languages)Equivalence relationCombinatoricsSpace (punctuation)Solution setPure mathematicsSet (abstract data type)Discrete mathematicsAlgorithmComputer science

Abstract

fetched live from OpenAlex

We explore the nature of the solution space for the Golomb nested recursion g(n)=g(n-g(n-1))+1. On this solution space, we define a natural equivalence relation and restrict our attention to non-equivalent solutions. We describe and prove an algorithm that determines whether a given set of initial conditions generates a solution. Up to equivalence, there is a unique solution whose forward differences are eventually either 0 or 1, namely, the Golomb sequence g0=1,2,2,3,3,3,4,4,4,4,⋯, generated by the initial condition g0(1)=1. This sequence is asymptotic to 2n; we conjecture that this is true of every solution. We further conjecture that each solution has what we call a generational structure that abstracts combinatorial properties of g0. It appears that for any given solution, its generations are composed of only a finite number of building blocks.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.005
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.244
Teacher spread0.223 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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