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Record W2588325964 · doi:10.3130/aija.70.41_2

A COMPARATIVE STUDY ON BUILDING PERFORMANCE EVALUATION METHODOLOGY

2005· article· en· W2588325964 on OpenAlexaboutno aff
P. Roux, Akikazu Kato, Kazuhisa TSUNEKAWA

Bibliographic record

VenueJournal of Architecture and Planning (Transactions of AIJ) · 2005
Typearticle
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Evaluation methodsEngineering managementComputer scienceEngineeringGeography

Abstract

fetched live from OpenAlex

This study, within the context of the IBPE (International Building Performance Evaluation) project, compares various methodological differences and similarities between IBPE, ASTM (American Society for Testing and Materials), and Japanese workplace planning standards and evaluation topics used for stating user-requirements and evaluating facility performance. Research findings presented in this paper resulted from ongoing research in Japanese workplace environments and Japanese BPE (Building Performance Evaluation) methodologies in collaboration with the International Center for Facilities in Canada. The study concludes with recommendations on certain measures that need to be taken to formulate a more standardized performance evaluation tool with greater cross-cultural applicability.

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)0.141
metaresearch head score (Gemma)0.196
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: Methods · Consensus signal: none
Teacher disagreement score0.141
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1410.196
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.010
Science and technology studies0.0020.002
Scholarly communication0.0040.006
Open science0.0010.003
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 head0.072
GPT teacher head0.327
Teacher spread0.255 · 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
GenreMethods

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

Citations2
Published2005
Admission routes1
Has abstractyes

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