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Record W4289263267 · doi:10.56069/2676-0428.2022.163

IMPACTOS DAS POLÍTICAS PÚBLICAS DE SAÚDE PARA OS IDOSOS NO BRASIL

2022· article· pt· W4289263267 on OpenAlexaff
Jeane Azevedo de Souza

Bibliographic record

VenueRevista Científica FESA · 2022
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsPolitical scienceGerontologyMedicine

Abstract

fetched live from OpenAlex

O presente artigo compõe-se de uma pesquisa qualitativa, com procedimentos de uma revisão bibliográfica da literatura nacional e internacional a respeito dos modelos de atenção integral à saúde dos idosos, como estratégias propostas pelas políticas públicas, em especial no Brasil. Esta pesquisa busca demonstrar de que forma as políticas públicas de saúde, elaboradas pelo Governo Federal, em consonância com os estados e municípios, têm acompanhado o envelhecimento da população, procurando apresentar soluções para as demandas que surgem com o processo de aumento da expectativa de vida, para que o envelhecimento seja acompanhado por uma maior qualidade de vida. Os resultados demonstram haver modelos inovadores para atenção integral aos idosos, especialmente focados nos cuidados de longo prazo, com o processo de atenção integral à saúde dos idosos. Os resultados demonstram que um dos grandes desafios para adequação, implementação e manutenção das estratégias de atenção integral para os idosos consiste em incluir a discussão sobre o envelhecimento da população brasileira nas agendas estratégicas das Políticas Públicas.

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)0.005
metaresearch head score (Gemma)0.016
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 score0.380
Threshold uncertainty score0.756

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.009
Science and technology studies0.0030.003
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.066
GPT teacher head0.430
Teacher spread0.363 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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Same venueRevista Científica FESASame topicHealth, Nursing, Elderly CareFrench-language works237,207