MétaCan
Menu
Back to cohort
Record W2099215784

E-PROCUREMENT IN THE ATLANTIC CANADIAN AEC INDUSTRY

2006· article· en· W2099215784 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Information Technology in Construction · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsProcurementVariety (cybernetics)Presentation (obstetrics)Fragmentation (computing)BusinessHousing industryEngineeringCritical success factorEngineering managementProcess managementMarketingIndustrial organizationComputer science
DOInot available

Abstract

fetched live from OpenAlex

Based on the success achieved in other industries, there is the potential for the Architectural, Engineering, and Construction industry to achieve significant improvements in efficiency through the adoption of e-business methods and solutions. There are a variety of issues that must be considered in steering the industry toward these improvements. The issues stem from the root characteristics of the industry including: fragmentation, highly pragmatic, cost conscious, little institutional leadership, and no standards in technology and business models. This paper examines e-procurement as a subset of e-business in an effort to identify the issues surrounding the development of a critical mass of participants required to overcome the organizational and technology challenges. The issues are discussed in some detail followed by the presentation of some preliminary results from a survey which quantifies the current status of the industry in an attempt to support a strategy for progress.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.294
Teacher spread0.272 · 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