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Record W3202523998 · doi:10.1109/icdcs51616.2021.00116

Demo: A FSM Approach to Web Collaboration

2021· article· en· W3202523998 on OpenAlexaff
Cristian Gadea, Bogdan Ionescu, Dan Ionescu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceCorrectnessFinite-state machineAutomatonCloud computingState (computer science)Transformation (genetics)Theoretical computer scienceModel transformationArchitectureSeries (stratigraphy)Programming languageDistributed computingSoftware engineeringOperating systemArtificial intelligence

Abstract

fetched live from OpenAlex

Operational Transformation (OT) algorithms, at the heart of web-based collaboration, have been studied since the late 1980s and remain a hot research subject. Centralized versions of OT algorithms that can be implemented on top of cloud-based serverless platforms are still unexplored. This poster introduces a Control Loop view of OT algorithms that are modeled by a series of Finite State Automata (FSAs) embedded in a serverless system architecture. A series of nested Finite State Machines (FSMs) dynamically control the co-editing processes. The proposed platform was simulated to demonstrate the correctness of the OT algorithms. Results obtained from the simulation are presented and an interactive demonstration is given.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2021
Admission routes1
Has abstractyes

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