MétaCan
Menu
Back to cohort

Translation and adaptation of the Premature Infant Pain Profile into Brazilian Portuguese

2013· article· en· W2104824141 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2013
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Toronto
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsPortugueseBrazilian PortugueseEquivalence (formal languages)Semantic equivalenceInternationalizationPsychologyLinguisticsMedicineArtificial intelligenceComputer scienceBusinessSemantic Web

Abstract

fetched live from OpenAlex

The study aimed to translate and to adapt a version of the Premature Infant Pain Profile into the Brazilian Portuguese language. This is a cross-sectional and methodological study for the validation of a translated version of a tool. The process was conducted in four stages: initial translation, synthesis, back-translation, and analysis by experts. Four independent versions of the instrument translated into Brazilian Portuguese were produced. Based on these initial translations, a synthesis version was developed. Two back-translated versions were independently produced, and none showed major differences compared to the original instrument. An expert committee reviewed the summary version and the back-translations with respect to semantic and idiomatic equivalence. The committee considered the translation into Brazilian Portuguese as appropriate. Therefore, the Perfil de Dor no Recém-Nascido Pré-termo was considered adapted to Brazilian Portuguese, for research purposes and for clinical practice. It will contribute to the internationalization of research results in Brazil.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.902
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.151
GPT teacher head0.383
Teacher spread0.232 · 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