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Record W2804371414 · doi:10.5539/mas.v12n6p44

Saving Travel Time as an Urban Planning Instrument. Case Study: Manizales, Colombia

2018· article· en· W2804371414 on OpenAlexvenueno aff
Carlos A. Moncada, Santiago Cardona

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Development and Innovation
Canadian institutionsnot available
FundersUniversidad Nacional de Colombia
KeywordsRing roadTravel timeGeographyTransport engineeringRegional scienceUrban infrastructureUrban planningCivil engineering

Abstract

fetched live from OpenAlex

This research explores the benefits of a proposal for urban road infrastructure which aims to improve road connection between northwest and western neighborhoods of the city of Manizales, Colombia, as well as to expand the ring of urban mobility that runs through the city. By calculating the global average accessibility and comparing the current and future situation, by averages of savings gradient, timesaving generated by this alternative are obtained in terms of average travel time. There is evidenced that suggest the road infrastructure proposal would generate savings in the average travel times for the entire city, especially to the neighborhoods located in the area of direct influence.

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: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.489

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.048
GPT teacher head0.324
Teacher spread0.277 · 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

Citations20
Published2018
Admission routes1
Has abstractyes

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