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Record W4396507754 · doi:10.55905/revconv.17n.4-267

Desafios do enfermeiro na atenção primaria à saúde: estudo reflexivo

2024· article· pt· W4396507754 on OpenAlexaff
Anicheriene Gomes de Oliveira Garbuggio, Monise Galante Paiva Gregorini, Simone Albino da Silva, Tayná Moura de Oliveira, Silvana Maria Coêlho Leite Fava, Namiê Okino Sawada, Maria Lúcia do Carmo Cruz Robazzi

Bibliographic record

VenueContribuciones a las Ciencias Sociales · 2024
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsPsychologyMedicineNursing

Abstract

fetched live from OpenAlex

Refletir sobre os desafios encontrados pelo enfermeiro diante de suas atribuições na Atenção Primária à Saúde no contexto das Práticas Avançadas de Enfermagem. Trata-se de um estudo teórico-reflexivo a partir de estudos encontrados de forma não sistemática, a fim de responder à questão norteadora:“Quais são os desafios que o enfermeiro atualmente encontra para desenvolver a gerência e assistência de qualidade no contexto da Atenção Primária à Saúde?” No exercício de liderança, o enfermeiro gestor promove um processo de trabalho flexível e acessível. No Brasil, apesar das iniciativas para desenvolver as Práticas Avançadas de Enfermagem, ainda há falta de clareza entre enfermeiros e médicos sobre sua definição, gerando conflitos e incertezas ético-legais. Os enfermeiros na Atenção Primária à Saúde enfrentam desafios significativos, mas superáveis. Ao valorizar o papel do enfermeiro e implementar políticas adequadas, é possível criar um ambiente favorável para que atue com eficácia, assegurando cuidado de qualidade à população.

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)0.058
metaresearch head score (Gemma)0.092
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.309

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.092
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0090.015
Scholarly communication0.0190.012
Open science0.0030.010
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.132
GPT teacher head0.440
Teacher spread0.307 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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