MétaCan
Menu
Back to cohort

Risco de quedas e a síndrome da fragilidade no idoso

2023· article· es· W4367728418 on OpenAlexaboutno aff
Adriana Luna Pinto Dias, Fabrícia Alves Pereira, Cláudia Paloma de Lima Barbosa, Gleicy Karine Nascimento de Araújo-Monteiro, Renata Clemente dos Santos, Rafaella Queiroga Souto

Bibliographic record

VenueActa Paulista de Enfermagem · 2023
Typearticle
Languagees
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGerontology

Abstract

fetched live from OpenAlex

Resumo Objetivo Analisar o risco de quedas e sua relação com a síndrome da fragilidade e variáveis sociodemográficas em idosos. Métodos Estudo transversal, analítico e multicêntrico, desenvolvido em dois hospitais universitários, no período de agosto de 2019 a janeiro de 2020, com 323 idosos, utilizando o Brazil Old Age Schedule (BOAS) para caracterização sociodemográfica, a Morse Fall Scale (MFS) para definição do risco de quedas e a Edmonton Frail Scale (EFS) para identificação da síndrome da fragilidade. Os dados foram [...]

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)0.001
metaresearch head score (Gemma)0.006
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.330
Teacher spread0.296 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueActa Paulista de EnfermagemSame topicFrailty in Older AdultsFrench-language works237,207