MétaCan
Menu
Back to cohort
Record W3080951141 · doi:10.15210/pixo.v4i13.19438

ANÁLISE SOCIOESPACIAL DA INFRAESTRUTURA DO ENTORNO RESIDENCIAL DO IDOSO EM FLORIANÓPOLIS

2020· article· pt· W3080951141 on OpenAlexaff
Vanessa Casarin, Fernanda Faccio Demarco, Fernanda Guasselli, German Gregório Monterrosa Ayala Filho

Bibliographic record

VenuePIXO - Revista de Arquitetura Cidade e Contemporaneidade · 2020
Typearticle
Languagept
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Têm-se consistentemente encontrado na literatura a presença de vegetação eacessibilidade como características desejáveis ao ambiente urbano. A acessibilidade, em especial, quando se trata da população idosa, para que tenha uma melhor qualidade de vida e condições de deslocamento. Assim, o objetivo central deste artigo é promover uma análise socioespacial da infraestrutura do entorno residencial do idoso no município de Florianópolis. A pesquisa utiliza dados do IBGE5, que são analisados estatisticamente e espacializados em mapas com auxílio do software QGis. Os resultados apontaram que a concentração de idosos em Florianópolis é maior em bairros de maior renda. Dentre os elementos infraestruturais analisados (presença de calçada, rampa, arborização urbana, iluminação pública e pavimentação e a ausência de lixo no logradouro público) o único que apresentou relação com a renda dos setores censitários foi a presença de calçada. A presença de rampa para acessibilidade e de arborização urbana ainda é bastante baixa na maioria dos setores censitários.Palavras-chave: entorno residencial, idoso, acessibilidade, áreas verdes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.005

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 head0.034
GPT teacher head0.275
Teacher spread0.241 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuePIXO - Revista de Arquitetura Cidade e ContemporaneidadeSame topicUrban Green Space and HealthFrench-language works237,207