MétaCan
Menu
Back to cohort
Record W2819044370 · doi:10.2991/ijndc.2018.6.2.4

Real-time Multi-Agents Architecture for E-commerce Servers

2018· article· en· W2819044370 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

Venue˜The œInternational journal of networked and distributed computing · 2018
Typearticle
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceServerArchitectureOperating systemDistributed computingEmbedded systemComputer architecture

Abstract

fetched live from OpenAlex

Electronic commerce applications have strict timing constraints on the interactions between e-commerce servers and customers.Customers prefer real-time services, which mean immediate response from the server shortly after submission of a request.This trend of demand gives e-commerce servers high pressure, both on the software and the architecture they currently use.In this paper, we propose a real-time architecture for e-commerce servers that addresses the problem efficiently.We adopt a framework that permits the appropriate treatment of dynamic behaviours that are data interdependent, and reasoning about the communication protocols and internal mechanisms of client / server relationships in a real-time multi-agents based e-commerce application architecture.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.568

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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