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Record W2137447276 · doi:10.1109/dsd.2007.10

A New Class of Cellular Automata

2007· article· en· W2137447276 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

VenueDigital Systems Design · 2007
Typearticle
Languageen
FieldComputer Science
TopicCellular Automata and Applications
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsCellular automatonMobile automatonBenchmark (surveying)Shift registerComputer scienceNeighbourhood (mathematics)AutomatonContinuous spatial automatonElectronic circuitAsynchronous cellular automatonAlgorithmFinite-state machineTheoretical computer scienceBuilt-in self-testTime complexityQuantum finite automataMathematicsAutomata theoryTelecommunications

Abstract

fetched live from OpenAlex

In this paper we present a new class of one-dimensional cellular automata which does not have the design complexity of two dimensional cellular automata but achieves higher fault coverage than the two most commonly used maximal length linear finite state machines: linear hybrid cellular automata and linear feedback shift registers. This class of cellular automata is based on a five-cell neighbourhood, giving it a much richer transition structure, but still keeping the interconnection complexity very low. A recurrence relation is given to enable the efficient calculation of the characteristic polynomial. The effectiveness of the new cellular automata is investigated by using them as generators for built-in self-test of the ISCAS 85 and ISCAS 89 benchmark circuits. While the resulting fault coverage is never worse than using the traditional linear feedback shift register as the generator, in about half of the circuits the fault coverage is significantly improved, in some cases by more than 20%.

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)0.000
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 score0.983
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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