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Record W4308632553 · doi:10.47820/recima21.v3i11.2133

TECNOLOGIAS DE GESTÃO DIGITAIS COMO SUBSÍDIO AO DESENVOLVIMENTO DE SERVIÇO HEMOTERÁPICO: PROTOCOLO DE REVISÃO DE ESCOPO

2022· article· pt· W4308632553 on OpenAlexaff
Marialdo Dias Barroso Mendonça, Maria Sálete Bessa Jorge

Bibliographic record

VenueRECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218 · 2022
Typearticle
Languagept
FieldSocial Sciences
TopicPublic Health in Brazil
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Objetivo: mapear na literatura científica e cinzenta, as tecnologias de gestão digitais como apoio ao desenvolvimento de serviços hemoterápicos na atenção especializada. Método: O protocolo seguirá as orientações do Joanna Briggs Institute- JBI, guiado pelo checklist PRISMA – ScR, que culminará em revisão de escopo. Os critérios de inclusão: serão publicações nos últimos 5 anos, nos idiomas português, inglês e espanhol, poderá ser legislação governamental. Critérios de exclusão: publicações pagas/fechadas, incompletas e/ou em fase de projeto ou ainda sem os resultados, que respondam à questão norteadora: “Quais as tecnologias de gestão digitais subsidiam o desenvolvimento de serviço hemoterápico?”. As fontes/bases de dados utilizadas serão: MEDLINE/ PubMed, SciELO/ BVS e Scopus, com uso de vocabulário estruturado e trilíngue indexado, DeCS - descritores em ciências da saúde e MeSH - Medical Subject Headings, com uso dos operadores booleanos/conectivos: OR e AND. Os estudos serão realizados por dois revisores independentes, por meio da plataforma de busca Rayyan. Os dados obtidos serão tabulados com uso do software NVivo, apresentados sob a forma de tabelas, quadros, figuras e/ou imagens.

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)0.020
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.005
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.005
Science and technology studies0.0080.002
Scholarly communication0.0020.001
Open science0.0060.004
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.057
GPT teacher head0.382
Teacher spread0.325 · 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
Published2022
Admission routes1
Has abstractyes

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Same venueRECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218Same topicPublic Health in BrazilFrench-language works237,207