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Record W2106145744 · doi:10.5555/510378.510656

Simphony: an integrated environment for construction simulation

2000· article· en· W2106145744 on OpenAlexaff
Simaan AbouRizk, Yasser Mohamed

Bibliographic record

VenueWinter Simulation Conference · 2000
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceAnimationSoftware engineeringSystems engineeringRepresentation (politics)User FriendlyComputer animationHuman–computer interactionEngineeringProgramming language

Abstract

fetched live from OpenAlex

This paper discusses Simphony as an integrated environment for building special purpose simulation tools for modeling construction systems. Simphony provides various services that enable the developer to easily control different behaviors in the developed tool such as simulation behaviors, graphical representation, statistics, and animation. These services allow the building of flexible and user-friendly tools in a relatively short time. The developed tools (templates) then provide the building blocks that a user (construction engineer) can use to create simulation models for different construction domains without the need for a deep background in simulation techniques. The services available for the developer are discussed and examples of their use are illustrated. Samples of the tools developed with Simphony are also reviewed to highlight some of their features.

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: Software · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.010

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 head0.240
Teacher spread0.221 · 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
GenreSoftware

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

Citations92
Published2000
Admission routes1
Has abstractyes

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