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2019· article· en· W4229839453 on OpenAlexfundno aff
Farzad Zarbakhsh, Jafar Yousefpour, Younes Karimpour Hayedi, Farhad Yadegari

Bibliographic record

VenueInternational Journal of Advanced Studies in Humanities and Social Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Landscape Design
Canadian institutionsnot available
FundersUniversity of TorontoU.S. Department of AgricultureNational Park ServiceU.S. Forest ServiceNational Science Foundation
KeywordsZoningEnvironmental planningUrban planningDisadvantagedSubdivisionLand-use planningLand useTransportation planningBusinessComprehensive planningRegional planningEnvironmental design and planningIntegrated business planningGeographyEconomic growthTransport engineeringCivil engineeringEngineeringEconomics

Abstract

fetched live from OpenAlex

How can one expect a rational growth and development of urban communities without a definite guide line for applying fixed elements on city planning such as Park? Introduction: City Planning; the unified development of cities and their environments. For most of its history, city planning dealt primarily with the regulation of land use and the physical arrangement of city structures, as guided by architectural, engineering, and land-development criteria. In the mid-1920th century it broadened to include the comprehensive guidance of the physical, economic, and social environment of a community.Elements characteristic of city planning include (1) General plans that summarize the objectives of land development; (2) Zoning and subdivision controls that specify permissible land uses, densities, and requirements for streets, utility services, and other improvements;(3) Plans for traffic flow and public transportation; (4) Strategies for economic revitalization of depressed urban and rural areas; (5) Strategies for supportive action to help disadvantaged social groups; and (6) Guidelines for environmental protection and preservation of scarce resources. City planning is conducted by governments on all levels—local, county, regional, state, and federal—and by private groups. It is also a subject of university-level study and Professional societies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.570
Threshold uncertainty score0.613

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5700.264

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 head0.072
GPT teacher head0.311
Teacher spread0.239 · 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.

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
Published2019
Admission routes1
Has abstractyes

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Same venueInternational Journal of Advanced Studies in Humanities and Social ScienceSame topicUrban Planning and Landscape DesignFrench-language works237,207