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Construção e validação de um índice para o planejamento da mobilidade com foco em polos geradores de viagens

2016· article· pt· W2575691485 on OpenAlexaff
Angélica Meireles de Oliveira, Antônio Nélson Rodrigues da Silva

Bibliographic record

VenueTransportes · 2016
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsMinistère des TransportsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Abordagens de planejamento destinadas a enfrentar os problemas de mobilidade associados aos grandes Polos Geradores de Viagens (PGVs) devem considerar as fases de diagnóstico, planejamento e avaliação das ações propostas. Esta é a estrutura da metodologia de sete etapas apresentada neste estudo, em que um índice de mobilidade sustentável é concebido para satisfazer necessidades locais. O objetivo deste artigo é discutir as diretrizes e procedimentos adotados para a construção e validação deste índice, estruturado em forma de um modelo hierárquico, bem como os resultados obtidos com a sua apli-cação em um campus universitário. A abordagem permitiu a identificação e avaliação dos principais fatores que afetam as condições de mobilidade do campus, além da associação destes aos diferentes modos de transporte. A importância da estra-tégia de validação foi evidenciada pela identificação de lacunas na estrutura do índice. Alguns ajustes foram então sugeridos, o que parece ser essencial para fazer do índice uma ferramenta também mais efetiva de planejamento.

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)0.010
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.107
GPT teacher head0.352
Teacher spread0.245 · 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 designSimulation or modeling
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

Citations2
Published2016
Admission routes1
Has abstractyes

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