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Record W2392986289

The analysis of international green residential district estimate systems——Taking the LEED,Chinese ecological residential technology assessment manual and others for example

2013· article· en· W2392986289 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

VenueSichuan Building Science · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Quality and Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsGreen buildingConstructiveProcess (computing)WeightingEvaluation methodsArchitectural engineeringEnvironmental resource managementEngineeringComputer scienceEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

The green residential assessment system is a comprehensively effective tool in guiding the construction development of residential environment.This article,compares the most representative international evaluation systems—American LEED,Canadian GBTOOL and Japanese CASBEE,Chinese ecological residential assessment manual and the Sino-Singapore green building standard—makes a comprehensive analysis from the aspects of evaluation key concept,evaluation content,evaluation weighting,evaluation process and so forth.The aim of this article is to point out what is crucial to be considered in the process of making the green residential assessment standard.Eventually putting forward to the constructive suggestion for green residential evaluation development based on the applicability research and the multi-level comparative analysis.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.015
GPT teacher head0.324
Teacher spread0.309 · 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