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Record W2254605759 · doi:10.1590/1982-0194201500067

Doenças raras: itinerário diagnóstico e terapêutico das famílias de pessoas afetadas

2015· article· pt· W2254605759 on OpenAlexaff
Geisa dos Santos Luz, Mara Regina Santos da Silva, Francine deMontigny

Bibliographic record

VenueActa Paulista de Enfermagem · 2015
Typearticle
Languagept
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversité du Québec en Outaouais
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMedicine

Abstract

fetched live from OpenAlex

Resumo Objetivo Caracterizar o itinerário diagnóstico e terapêutico realizado pelas famílias de pessoas com doenças raras, no âmbito da rede de serviços públicos brasileiros. Métodos Trata-se de pesquisa qualitativa. Utilizou-se a teoria bioecológica do desenvolvimento humano, de Urie Bronfenbrenner, para a compreensão dos dados. O instrumento de pesquisa foi uma entrevista semiestruturada, e os dados foram analisados pelo método de análise de conteúdo. Resultados Foram agrupados três núcleos temáticos: “Itinerário das famílias em busca do diagnóstico da doença”; “Itinerário das famílias no pós-diagnóstico da doença”; “Itinerário de manutenção terapêutica”. Conclusão O acesso aos serviços especializado possibilitou a obtenção do diagnóstico da doença rara. O tratamento foi um desafio, pois há poucos medicamentos disponíveis na escolha terapêutica para essas doenças. A judicialização foi fundamental para o acesso e a manutenção terapêutica.

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)0.004
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.315
Teacher spread0.281 · 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".

Quick stats

Citations29
Published2015
Admission routes1
Has abstractyes

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