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Record W2361028555

Structural Design of No.10 Building in Tianshui Fenlukou Residential Quarter

2011· article· en· W2361028555 on OpenAlexaboutno aff
Bin He

Bibliographic record

VenueJournal of Water Resources and Architectural Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicSimulation and Modeling Applications
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Architectural engineeringBuilding designStructural systemFrame (networking)ResidenceEngineeringArchitectureArchitectural designFoundation (evidence)Building constructionCivil engineeringScheme (mathematics)Structural engineeringMechanical engineeringGeographyMathematicsSociology
DOInot available

Abstract

fetched live from OpenAlex

This project is the structural design of No.10 Building in Tianshui Fenlukou Residential Quarter.Its one to second floor is a kindergarten,three to six is for residence;at the same time,its main body is a six-layers structure,and the local is a seven-layers structure.In the design,two parts are included such as the architectural design and structural design.Architectural Design: According to the given requirements and specifications,the architectural design of No.10 Building would be made,then the building scheme drawing and construction drawing would be made.Structural Design: First,according to the building scheme drawing,the structural selection would be carried out,then,by using the frame structure and based on the local natural and geographical conditions as well as the building scheme drawing,the calculations of the foundation and main structure would be made,at last,the structural construction drawing would be completed.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.001

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 head0.017
GPT teacher head0.204
Teacher spread0.187 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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