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Project Performance Control in Reconstruction Projects

2000· article· en· W1982161115 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

VenueJournal of Construction Engineering and Management · 2000
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsScheduleControl (management)Quality (philosophy)Earned value managementProcess managementPerformance indicatorEngineeringProject planningConstruction engineeringEngineering managementComputer scienceProject managementTransport engineeringOperations managementSystems engineeringBusinessProject charterArtificial intelligenceMarketing

Abstract

fetched live from OpenAlex

Cost, schedule, and quality are the main indicators of performance in construction projects. These indicators are highly interrelated and require some balance and trade-off among them to achieve efficient overall control over project performance. Focusing on these performance indicators, the primary objective of this study is to investigate the use of conventional control techniques in projects involving reconstruction of occupied buildings. To facilitate this analysis, performance data have been collected, using a questionnaire survey, from 25 reconstruction and 15 new construction projects. The survey was followed by structured interviews with construction practitioners and project participants to elicit success-related factors and to identify some of the unique problems affecting the control of reconstruction projects. Using the collected data, performance comparison was conducted between new and reconstruction projects along with a detailed analysis of the suitability of existing techniques for the control of the cost, schedule, and quality in reconstruction projects.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.171
Teacher spread0.167 · 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