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Record W2621282487

Termination in finite mean time of a CSMA/CA rule-based model

2006· article· en· W2621282487 on OpenAlexaff
Olivier Bournez, Florent Garnier, Claude Kirchner

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2006
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsPrevention of Organ Failure
Fundersnot available
KeywordsProbabilistic logicComputer scienceProtocol (science)AlgorithmTheoretical computer scienceDistributed computingArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

In a recent work, we introduced the notion of probabilistic rewrite system, and we proposed techniques to prove termination of such systems in finite mean time. In this paper, we model with probabilistic rewrite rules a WI-FI stations network running the CSMA/CA 802.11b protocol. Following this model and using the previously proposed framework, we prove that the protocol terminates in a finite mean time.

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)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0020.005
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 head0.006
GPT teacher head0.186
Teacher spread0.180 · 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 designSimulation or modeling
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
Published2006
Admission routes1
Has abstractyes

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