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Record W4235291268 · doi:10.22215/etd/2018-13204

Properties of Interleaved Sequences Created from M-Sequences

2018· dissertation· en· W4235291268 on OpenAlexaff
Kirsten Nelson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
Topicgraph theory and CDMA systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsPalindromeSequence (biology)MathematicsBase (topology)CombinatoricsTupleComplementary sequencesEquivalence (formal languages)Discrete mathematicsGeneticsBiologyMathematical analysis

Abstract

fetched live from OpenAlex

Maximal-length sequences or m-sequences over a finite field F q are a wellknown and studied class of sequences with desirable properties such as balance of both individual elements and tuples.Interleaved sequences are created by combining a base sequence a of period s and a shift sequence e of length T , consisting of elements from Z q ∪ {∞}.This thesis examines interleaved sequences to determine which properties of m-sequences are preserved when the m-sequence is used as a base sequence.First an equivalence relation on shift sequences is defined, with two operations that can be applied to these sequences.Palindromic sequences are defined, and the exact conditions for the interleaved sequence to also be palindromic are given.The period of the interleaved sequence was previously known to divide sT , but this thesis proves that the length of the interleaved sequence can be l then, letting n = sT /l we must have n | T and gcd(n, s) = 1.The results of experimentation on using the interleaved sequences to construct covering arrays are given.

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)0.005
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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Same topicgraph theory and CDMA systemsFrench-language works237,207