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Record W2081025098 · doi:10.5539/ass.v5n8p144

Study on Construction Cost of Construction Projects

2009· article· en· W2081025098 on OpenAlexvenueno aff
Hui Li

Bibliographic record

VenueAsian Social Science · 2009
Typearticle
Languageen
FieldEngineering
TopicEvaluation and Optimization Models
Canadian institutionsnot available
Fundersnot available
KeywordsCost engineeringConstruction managementPre-construction servicesControl (management)Status quoCost controlQuality (philosophy)Investment (military)Construction engineeringRisk analysis (engineering)Value engineeringCost accountingCost estimateProcess (computing)Cost contingencyQuality costsChinaProject managementEngineering managementBusinessEngineeringOperations managementComputer scienceProject management triangleCivil engineeringSystems engineeringEconomicsAccounting

Abstract

fetched live from OpenAlex

China is a country which has the largest investment amount in engineering construction in the world and which has the most construction projects. It is a significant subject for the extensive engineering managers to have effective engineering cost management in construction project management and to reasonably determine and control construction cost on the condition of ensuring construction quality and time limit.On the basis of the status quo of losing control in Chinese construction investment and of separation of technique and economy in engineering, and guided by basic theories of construction cost control, the author discusses control methods and application of construction cost, sets forth existing issues in construction cost control and influences of these issues on determination and control of construction cost, puts forward that construction cost control should reflect cost control of the entire construction process at the earlier stage of construction, and then introduces some procedures and methods of applying value project cost control at all stages of construction 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.

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)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.311
Teacher spread0.277 · 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 designObservational
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

Citations11
Published2009
Admission routes1
Has abstractyes

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