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Record W2884923533 · doi:10.5539/mas.v12n8p27

Parameters for Public Space Architecture. Informal Commerce Dynamics, as an Opportunity to Stimulate Urban Scenarios. Case Study Cali-Colombia

2018· article· en· W2884923533 on OpenAlexvenueno aff
Gustavo Adolfo Arteaga Botero, Edier Segura, Diego A. Escobar

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology in Learning
Canadian institutionsnot available
Fundersnot available
KeywordsPedestrianArchitectureSpace (punctuation)Government (linguistics)Public spaceCenter (category theory)Economic JusticeForcing (mathematics)Social justicePopulationSocial dynamicsDynamics (music)GeographyEconomic growthPolitical sciencePublic administrationEconomic geographySociologyPolitical economyArchitectural engineeringEconomicsEngineeringLawComputer scienceSocial scienceArchaeologyDemographyGeology

Abstract

fetched live from OpenAlex

In the last decades, the occupation of the pedestrian routes and in general of the public space in the city center of Cali Colombia, have been evidencing diverse phenomena, which to a great extent respond to the accelerated growth of the urban population, where the migrations that have occurred in the interior of the country (fruit of the social conflicts of the last decades), have particularly marked the realities. In Cali, on 10th and 15th streets, near the Government Building, the Palace of Justice and the Municipal Administrative Center - CAM, the public space in general terms has been stressed in a particular way, which has generated conflicts in the surfaces designed for the pedestrians, since they are occupied by vendors in the midst of the informality routines, forcing the pedestrian to use the automobile tracks being a notorious and interesting phenomenon, when observing the factors that produce it and using them as parameters in the design of architectural spaces that contribute to improvement.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.051
GPT teacher head0.322
Teacher spread0.271 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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