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Record W2118804107 · doi:10.1002/rsa.20095

The Boolean functions computed by random Boolean formulas or how to grow the right function

2005· article· en· W2118804107 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

VenueRandom Structures and Algorithms · 2005
Typearticle
Languageen
FieldComputer Science
Topicsemigroups and automata theory
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
Fundersnot available
KeywordsBoolean functionProbabilistic logicMonotone polygonFunction (biology)MathematicsDiscrete mathematicsConvergence (economics)CombinatoricsComputer scienceTheoretical computer scienceStatistics

Abstract

fetched live from OpenAlex

Abstract We characterize growth processes (probabilistic amplification) by their initial conditions to derive conditions under which results such as Valiant's J Algorithms 5 (1984), 363–366 hold. We completely characterize growth processes that use linear connectives and generalize Savický's Discrete Math 147 (1990), 95–103 analysis to characterize growth processes that use monotone connectives. Additionally, we obtain explicit bounds on the convergence rates of several growth processes, including the growth process studied in Savický. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2005

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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