MétaCan
Menu
Back to cohort

Avaliação das dimensões da dor no paciente oncológico

2020· article· pt· W3080669861 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.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNursing Edição Brasileira · 2020
Typearticle
Languagept
FieldMedicine
TopicPalliative and Oncologic Care
Canadian institutionsnot available
FundersMcGill University
KeywordsHumanitiesMedicinePhilosophy

Abstract

fetched live from OpenAlex

Objetivo: mensurar a experiência dolorosa em pacientes oncológicos. Método: pesquisa transversal, descritiva de abordagem quantitativa, com 50 pacientes que realizam tratamento oncológico em um serviço privado localizado na região Noroeste do Estado do Rio Grande do Sul, após aprovação do Comitê de Ética em Pesquisa sob protocolo CAAE nº 14025119.0.0000.5354. O instrumento escolhido foi o Questionário da Dor McGill. Os dados foram armazenados no Microsoft Office Excel e analisados através da estatí­stica descritiva. Resultados: Prevalência do sexo feminino (54%) e câncer de Cólon (20%). Os descritores mais usados foram: Fisgada (54%), Cansativa (52%), Chata (38%) e Aperta (26%) e 80% dos pacientes relataram ausência de dor no momento da entrevista. Conclusão: O Questionário da Dor McGill permite conhecer os aspectos qualitativos da dor, além de dar suporte í enfermagem no planejamento da assistência ao paciente, oferecendo melhora na qualidade da sistematização da assistência de enfermagem.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.005

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 head0.095
GPT teacher head0.381
Teacher spread0.286 · 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