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Record W2368168412

Curitiba: the City for People,Not for Car:How to Build the Livable Cities in Developing Country

2015· article· en· W2368168412 on OpenAlexaboutno aff
Deng Zhi-tua

Bibliographic record

VenueChengshi fazhan yanjiu · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Development and Societal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsCuritibaTransport engineeringPublic transportUrban planningCity logisticsBusinessEnvironmental planningEconomic growthGeographyRegional scienceCivil engineeringEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

Up to 3 /4 of commuters take bus in Curitiba Brazile. It was chosen as the most livable city by the United Nations tied with Paris,Vancouver,Sydney and Rome. It has a good urban planning,good public transportation systems,good waste management and better environmental protection. What had happened during last 40 years? In simple word,Curitiba had solved the core problem of urban development: traffic,green space and waste disposal. This is an important reference to the most Chinese cities because of the same city problem in terms of a lower level of economic development.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.197
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.094
GPT teacher head0.326
Teacher spread0.232 · 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 designQualitative
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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