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Record W2139392516 · doi:10.1061/41109(373)139

An Integrated Condition Assessment Model for Buildings

2010· article· en· W2139392516 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

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicFacilities and Workplace Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsWork (physics)Process (computing)Asset (computer security)Facility managementService (business)Asset managementArchitectural engineeringBuilding managementRisk analysis (engineering)Computer scienceEnvironmental resource managementEnvironmental planningBusinessEngineeringEnvironmental scienceComputer security

Abstract

fetched live from OpenAlex

Building facilities are a major part of urban infrastructure, as they provide shelter, living space, and service areas to accommodate human activity. Despite their great economic, cultural and historical importance, many studies have shown that buildings are sick, deteriorating and considered to be a major source of pollution. Lack of funds and mismanagement are the principle reasons for the unsatisfactory performance of building facilities. Maintaining a building is essential to keep it performing and functioning for a longer period of time. Despite the importance of the condition assessment (CA) stage in the asset management process, a literature review reveals that there is no building assessment framework that considers both physical and environmental conditions. The objective of this paper is to develop an integrated CA model that integrates both the physical and environmental aspects of buildings. This model provides an accurate, reliable, and sustainable framework capable of assessing a building from both physical and environmental perspectives. The framework is to be implemented and tested using data collected from experts as well as from operation systems for existing office buildings in North America. Details of the proposed framework and its implementation are presented. The research work in this paper assists facility managers and owner's organizations in administrating such buildings.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.831
Threshold uncertainty score0.997

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)0.0040.000

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 head0.021
GPT teacher head0.360
Teacher spread0.339 · 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

Quick stats

Citations16
Published2010
Admission routes1
Has abstractyes

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