MétaCan
Menu
Back to cohort

Improving Design Coordination for Building Projects. II: A Collaborative System

2001· article· en· W2036178893 on OpenAlexaff
Essam Zaneldin, Tarek Hegazy, Donald E. Grierson

Bibliographic record

VenueJournal of Construction Engineering and Management · 2001
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceProcess (computing)The InternetDomain (mathematical analysis)Collaborative designInformation sharingBuilding information modelingDesign technologySystems designSystems engineeringEngineering managementKnowledge managementSoftware engineeringWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

The objective of this paper is to utilize recent advances in information technology and computer collaboration tools to improve coordination and increase productivity in the design of building projects. Based on a structured information model, presented in a companion paper, a collaborative design system is developed incorporating (1) a client-server environment for representing building data, recording design rationale, and effectively managing design changes; and (2) Internet-based collaboration tools for sharing documents, reviewing changes, and conferencing among remote design participants. Implementation issues and the perceived changes imposed on the traditional design process are discussed, and an example application is worked to demonstrate the applicability and features of the developed prototype. The developments made in this paper provide guidelines for modeling complex information-dependent processes in the construction domain.

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)0.008
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0020.006
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.007
GPT teacher head0.192
Teacher spread0.185 · 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 designNot applicable
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

Citations39
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Construction Engineering and ManagementSame topicBIM and Construction IntegrationFrench-language works237,207