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Record W2233210616

An Integrated Condition Assessment Model for Educational Buildings Using BIM

2012· dissertation· en· W2233210616 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2012
Typedissertation
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsAnalytic hierarchy processBuilding information modelingProcess (computing)Facility managementAsset (computer security)EngineeringService (business)Asset managementArchitectural engineeringQuality (philosophy)Computer scienceCivil engineeringRisk analysis (engineering)Operations researchBusinessOperations management
DOInot available

Abstract

fetched live from OpenAlex

Building facilities compose a major part of any urban infrastructure. Despite their considerable economic, cultural and/or historic importance, several studies have shown that many buildings are sick, deteriorating and a major source of pollution. Maintaining a building is essential to keep it performing and functioning for a longer period of time as well as providing better quality of life for building occupants. Despite the importance of the condition assessment (CA) stage in the asset management process, literature review reveals that there is no building condition assessment framework that considers both physical and environmental conditions. Schools and educational facilities in Canada, which comprise a major component of the non-residential buildings sector, has passed 51% of their useful service life
\n The primary objective of this research is to develop an Integrated Condition Assessment Model for Educational Buildings that considers both building physical and environmental conditions. This model will assist owners and facility managers in the condition assessment phase during the asset management process. As buildings are composed of spaces; this proposed model uses “space” as the principal element of evaluation. The Multi Attribute Utility Theory (MAUT) is used to calculate the physical and environmental conditions of each space, and the K-mean clustering is conducted to calculate the integrated condition of each one. Data are collected from experts via questionnaires to assign relative weights to models’ attributes using both the Analytical Network Process (ANP) and the Analytical Hierarchy Process (AHP) techniques. The proposed methodology upgrades the use of an object-oriented Building Information Model (BIM) so that it can be used as a platform and an advanced tool for storing, exchanging, and transferring assessment data inputs as well as serving in the assessment process. Integrated Condition Assessment model for Buildings (ICAB) is the developed automated tool that integrates with Revit© 2011. This integration allows the BIM model to be used as the data source and to provide any required graphical representation. 
\nThe model is implemented and tested using data collected from experts and from field measurements taken from an educational building in Montreal. Finally, the model was validated by experts working in the facilities management field and they acknowledged having good potentials.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.031
GPT teacher head0.318
Teacher spread0.288 · 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