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Record W4231307182 · doi:10.29173/mocs145

The Regional Industrial Symbiosis Model for Industrialized Construction Ecosystem

2015· article· en· W4231307182 on OpenAlexvenueno aff
Guiwen Liu, Kai-jian Li, Yue Teng

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2015
Typearticle
Languageen
FieldEngineering
TopicSustainable Industrial Ecology
Canadian institutionsnot available
FundersChongqing Graduate Student Research Innovation ProjectFundamental Research Funds for the Central Universities
KeywordsNewly industrialized countryIndustrial symbiosisChinaGovernment (linguistics)BusinessSustainable developmentProductivityDeveloped countryEnvironmental economicsIndustrial organizationEnvironmental resource managementDeveloping countryEconomic growthEcologyEconomicsPolitical science

Abstract

fetched live from OpenAlex

Industrialized construction, which utilizes principles associated with factory production, can considerably improve productivity, quality, and service life of building while reduce cost, energy consumption and environmental impact. China government has committed sustainable development and promoted industrialized construction through legislative acts. The number of industrialized public houses in China has rapidly grown to over 3 million per year. However, the ecosystem of industrialized construction of China is still in the infant stage: hesitating stakeholders, sporadic manufacturing, and incomplete industry chain. The aim of this paper is thus to achieve an in-depth understanding of the whole ecosystem of industrialized construction in China. There are four research objectives of this paper: (1) to analyze the symbiotic mechanisms of it based on industrial ecology theory; (2) to build the Regional Industrial Symbiosis (RIS) model of industrialized construction ecosystem based on synergetics theory; (3) to explore the evolutionary trajectories based on the RIS model by simulating the evolutionary trajectory of symbiotic units and analyzing the stable symbiotic point. This paper presented the symbiotic mechanism and four relationships between the populations of industrialized construction ecosystem. It could contribute to the prediction of the evolutionary trajectory of industrialized construction and achieve the policy formulation and implementation.

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 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)0.001
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 score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.051
GPT teacher head0.224
Teacher spread0.173 · 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 teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations1
Published2015
Admission routes1
Has abstractyes

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