Prevalência e fatores sociodemográficos associados à fragilidade em mulheres idosas
Bibliographic record
Abstract
Cross-sectional study that aimed to estimating the prevalence of frailty in older women living in the city of João Pessoa, Paraíba, Brazil; and to identify possible associations between frailty and socio-demographic variables. The sample included 166 elderly women were interviewed in their home between April and June 2011. For data was collected using a structure instrument to questions on socio-demographic variables and the Edmonton Frail Scale. The descriptive data analysis, performed by SPSS 15.0, showed that most elderly women 60.8% showed some degree of fragility. Among them, 21.7% were apparently vulnerable, 23.5% mild frailty, 7.8% moderate and 7.8% severe frailty. It was found an association of the phenomena with age, education and income, conditions under which nurses must act in order to prevent the event.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".