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Record W2032261263 · doi:10.1142/s0129054107005303

SOLITON AUTOMATA BASED ON TREES

2007· article· en· W2032261263 on OpenAlexafffund
Helmut Jürgensen, PAULINE KRAAK

Bibliographic record

VenueInternational Journal of Foundations of Computer Science · 2007
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMonoidAutomatonTree (set theory)MathematicsQuantum finite automataDiscrete mathematicsSolitonTree automatonAutomata theorySet (abstract data type)CombinatoricsComputer sciencePhysicsTheoretical computer scienceNonlinear systemQuantum mechanics

Abstract

fetched live from OpenAlex

Soliton automata are a mathematical model for molecular switching devices. For even the simple case of soliton automata based on trees the behaviour is not known. For example, only two examples of such soliton automata were known the transition monoid of which is not the symmetric group on the set of states; and in these cases the transition monoid is the corresponding alternating group. We establish new bounds on the number of states of a tree-based soliton automaton and a sufficient condition for when the transition monoid of such a soliton automaton consists only of even permutations of the set of states. We also summarize the results of a systematic enumeration of tree-based soliton automata by which additional exceptions were found, each an alternating group in its natural representation.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.267
Teacher spread0.259 · 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

Citations1
Published2007
Admission routes2
Has abstractyes

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