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Record W2108869243 · doi:10.1109/icsmc.1995.537892

Mediator: an intelligent information system supporting the virtual manufacturing enterprise

2002· article· en· W2108869243 on OpenAlexafffund
B.R. Gaines, Douglas H. Norrie, Andrew Z. Lapsley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Database Systems and Queries
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceProduct lifecycleInterface (matter)Process (computing)Function (biology)MediatorUser interfaceKnowledge managementProcess managementNew product developmentEngineeringBusiness

Abstract

fetched live from OpenAlex

Mediator is an open architecture information and knowledge management system designed to provide a flexible technology to support the management of complex manufacturing activities throughout the product life cycle. A heterogeneous environment is assumed in which the sub-systems are geographically dispersed and involve different application packages, not necessarily designed to work together, multiple platforms, protocols and forms of user interface. The function of Mediator is to provide a knowledge support system for all those involved in the manufacturing process from requirements through design, engineering, production, to maintenance and recycling. It is designed to facilitate communication, compliance with constraints including physical restrictions and legal obligations, and to generally represent knowledge about any activity or subsystem relevant to the manufacturing process. This paper reports on a second-generation Mediator implementation based on World-Wide-Web protocols and browsers augmented by specialist helper and server applications.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0030.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.005

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 head0.015
GPT teacher head0.228
Teacher spread0.214 · 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

Citations45
Published2002
Admission routes2
Has abstractyes

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