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Dynamics of the Cellular Automaton Rule 142

2005· article· en· W2963381224 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComplex Systems · 2005
Typearticle
Languageen
FieldComputer Science
TopicCellular Automata and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCellular automatonComputer scienceStochastic cellular automatonBlock cellular automatonElementary cellular automatonContinuous automatonAsynchronous cellular automatonDeterministic automatonLattice gas automatonAutomatonDynamics (music)Theoretical computer scienceMobile automatonArtificial intelligencePhysicsAutomata theory

Abstract

fetched live from OpenAlex

We investigate dynamics of the cellular automaton Rule 142. This rule possesses additive invariant of the second order, namely it conserves the number of blocks "10." Rule 142 can be alternatively described as an operation on a binary string in which we simultaneously flip all symbols which have dissenting right neighbors. We show that the probability of having a dissenting neighbor can be computed exactly using the fact that the surjective Rule 60 transforms Rule 142 into Rule 226. We also demonstrate that the conservation of the number of 10 blocks implies that these blocks move with speed -1 or stay in the same place, depending on the state of the preceding site. At the density of blocks 10 equal to 0.25, Rule 142 exhibits a phenomenon similar to the jamming transitions occurring in discrete models of traffic flow.

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: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.294

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 communication0.0000.000
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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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