MétaCan
Menu
Back to cohort
Record W2068999475 · doi:10.1108/14714170310814882

A decision support tool for construction bidding

2003· article· en· W2068999475 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

VenueConstruction Innovation · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsConcordia University
FundersNational Science Council
KeywordsBiddingMarkup languageComputer scienceProcurementAnalytic hierarchy processDecision support systemConstruct (python library)Process (computing)Construction biddingDecision analysisDecision makerDecision modelOperations researchSystems engineeringProject managementEngineeringBusinessData miningMachine learningXMLPre-construction servicesMarketingEconomicsProject planningWorld Wide Web

Abstract

fetched live from OpenAlex

A reliable estimate of markup is essential for successful bid proposals. This paper presents a decision support model for construction bidding. The developed model can assist contractors in estimating markup, and owners and/or their agents in evaluating bid proposals. The model is generic and can be used as a tool to evaluate different alternatives in engineering, procurement, and construction. It utilizes the multi‐attribute utility theory and the analytic hierarchy process and makes use of their advantages. Unlike models developed for similar purposes, the proposed model provides a decision support environment for the two functions; that is, estimating markup and evaluating bids. It also enables the user to construct the decision hierarchy that best suits his/her company’s business environment and bidding strategy in a flexible manner. It accounts for the decision maker’s attitude towards risk. Two numerical examples are presented to demonstrate the use and capabilities of the proposed model.

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)0.006
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.152
GPT teacher head0.425
Teacher spread0.273 · 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