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Record W2612131327

The BELCAM Project: a summary of three years of research in service life prediction and information technology

2002· article· en· W2612131327 on OpenAlexafffundvenueabout
Zoubir Lounis

Bibliographic record

VenueNPARC · 2002
Typearticle
Languageen
FieldPsychology
TopicFacilities and Workplace Management
Canadian institutionsPublic Works and Government Services CanadaNatural Sciences and Engineering Research Council of Canada
FundersConcordia UniversityNational Research Council CanadaMinistère de la Défense NationaleU.S. Army Corps of EngineersPublic Works and Government Services CanadaRyerson University
KeywordsEnvelope (radar)Asset (computer security)Service (business)Reliability engineeringEngineeringOperations researchBuilding information modelingComputer scienceRisk analysis (engineering)Operations managementRadar
DOInot available

Abstract

fetched live from OpenAlex

This paper summarizes the first stage of research for the Building Envelope Life Cycle Asset Management (BELCAM) Project for developing techniques to predict the remaining service life of building envelope components and procedures to optimize their maintenance. Data were collected on 2800 roof sections from a wide range of systems and climatic regions across Canada according to age, material type, geographic location and condition of the roofing sections. Techniques were developed for estimating the life cycle costs for different maintenance strategies and the risk of envelope failure and a prototype, graphical, decision-support tool was developed.

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)0.006
metaresearch head score (Gemma)0.007
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 score0.242
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.044
GPT teacher head0.300
Teacher spread0.257 · 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

Citations6
Published2002
Admission routes4
Has abstractyes

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