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Record W3207654191 · doi:10.17271/19843240143220212882

Impactos Pandêmicos ao Turismo de zonas geográficas litorâneas, estratégias de prevenção para o litoral norte.

2021· article· pt· W3207654191 on OpenAlexaff
Alessandra dos Santos Costa, Carlos Andrés Hernández Arriagada

Bibliographic record

VenueRevista Científica ANAP Brasil · 2021
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

A presente investigação busca compreender as novas faces do turismo no período do ano de 2020 em decorrência da falência dos processos econômicos, sociais e territoriais na escala geográfica do Litoral Norte, tendo como caso de estudo a cidade de Ilhabela, no litoral brasileiro. Este fenômeno que assolou globalmente diversas sociedades e zonas urbanas cujas características de alta volatilidade propiciou a necessidade por meio das novas interações humanas, diversas adaptações aos serviços e gerações econômicas ao longo do mundo. A fenomenologia deste fato é oriunda do processo pandêmico ocasionado pelo COVID-19, impactando os meios de sobrevivência, as zonas urbanas e suas diversas escalas produtivas e gerando uma fragmentação entre o consumo da imagem de um território, o atrativo da sobrevivência humana baseado no ócio e o grande número de redução de conectividades entre zonas de alta demanda turística. O trabalho se colocou em compreender a macro situação e ensaiar soluções temporais por meio de estratégias que permitam ao longo deste período propiciar melhorias estruturais e fomentar novos protocolos para a saúde pública. Assim, o caso de Ilhabela se coloca como um possível expoente para um modelo nacional de combate pandêmico em zonas litorâneas brasileiras.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.044
GPT teacher head0.336
Teacher spread0.292 · 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 teacher head, not a consensus.

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRevista Científica ANAP BrasilSame topicHealthcare during COVID-19 PandemicFrench-language works237,207