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Inspirations to the Construction of Chinese Cities from City of Waterloo – Garden City of the 21st Century

2015· article· en· W1976242733 on OpenAlexaboutno aff
Hui Zhao

Bibliographic record

VenueApplied Mechanics and Materials · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSustainable Urban and Rural Development
Canadian institutionsnot available
Fundersnot available
KeywordsChinaChinese cityService (business)Industrial cityGeographyCivil engineeringFace (sociological concept)Space (punctuation)Environmental planningTransport engineeringRegional scienceArchitectural engineeringEconomySociologyEngineeringArchaeologySocial scienceComputer scienceIndustrial zone

Abstract

fetched live from OpenAlex

Face of China's urban problems, we have been thinking how to build a healthy and livable city. The City of Waterloo in Canada, a modern version of Garden City, has given us some inspirations. Briefly summarize the situation of Garden City and the City of Waterloo, analyze detailed why we say the City of Waterloo is Garden City of the 21st century, and point out that they are the same in essence, which is a city with the advantages of both town and country. It shows that it is not impossible to build a healthy and livable city with both advantages in the contemporary. Finally, give a clear explanation of inspirations to the construction of Chinese cities from the City of Waterloo. The inspirations are the followings. The layout of city should conform to the nature; City should give priority to green traffic; Urban commercial, culture, and other service facilities may lay out with appropriate centralized and decentralized; Open Space should retain appropriate original landscape.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.801
Threshold uncertainty score0.396

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0080.011
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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
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
Published2015
Admission routes1
Has abstractyes

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