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Record W2098559241 · doi:10.5555/2693848.2694254

Lifecycle evaluation of building sustainability using BIM and RTLS

2014· article· en· W2098559241 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

VenueWinter Simulation Conference · 2014
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsConcordia University
Fundersnot available
KeywordsReal-time locating systemBuilding information modelingSustainabilityInteroperabilitySystems engineeringComputer scienceInformation modelEngineeringProcess managementSoftware engineeringOperations managementReal-time computingWorld Wide Web

Abstract

fetched live from OpenAlex

The purpose of this research is to provide a lifecycle building sustainability evaluation method to guide different stakeholders in how to apply sustainable practices and maintain the expected sustainability. Building Information Modeling (BIM) is selected to be a platform to integrate all the information to improve interoperability. Green standards are embedded in the BIM model and a rule-based system is developed to automatically evaluate the design and the building performance. Data are collected by using a Real-Time Location System (RTLS) and are used to update the BIM model. The as-built model is checked to see if it matches the sustainability aspects regarding the construction processes. During operation, energy consumption data are collected and analyzed. The performance of the building is checked to see if the designed features reach the sustainability goals. By integrating the BIM, RTLS, and other information, a prototype system of lifecycle sustainability evaluation is developed and tested.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.308

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)0.0000.000

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 head0.037
GPT teacher head0.307
Teacher spread0.270 · 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