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.
Bibliographic record
Abstract
This study aimed at analyzing the physiological factors affecting functional performance of knee osteoarthritis in elderly patients and to build a structural model for explaining and predicting functional performance. A hypothetical model was formulated through a literature review. The research variables were five exogenous variables (severity of knee osteoarthritis, age, degree of obesity, symptoms of knee osteoarthritis, and functional capacity) and three endogenous variables (symptoms of knee osteoarthritis, functional capacity, and functional performance). \n The subjects consisted of 315 elderly patients with knee osteoarthritis who were more than 60 years old and registered at orthopaedic hospitals in D city. The data were collected from July 2 through 28 2012. Symptom levels of knee osteoarthritis were measured using the Korean-Western Ontario and McMaster Universities (K-WOMAC) questionnaire, and functional capacity was measured using the Timed Up and Go (TUG) test. Functional performance was measured using the Functional Performance Inventory–Short Form (FPI-SF) questionnaire developed by Leidy & Knebel (2010). Finally, the severity of knee osteoarthritis was measured using Kellgren-Lawrence (K-L) grade, and obesity levels were measured using Body Mass Index (BMI). \n The data were analyzed with SPSS 19.0 using descriptive statistics, Pearson correlation coefficient, and exploratory factor. Confirmatory factor analysis, the goodness-of-fit of the hypothetical model, and the hypotheses were measured using AMOS 19.0. \n The results of this study were as follows; \n 1. The accessibility scores of the final model were x²=139.373, df=46, p<.001, GFI=.929, AGFI=.879, RMSEA=.080, NFI=.854, IFI=.897, CFI=.895, and AIC=203.373. The data and the framework fitted the functional performance model. \n 2. All indices of goodness-of-fit in the hypothetical model were accepted. Ten of the 15 hypotheses were supported. \n In conclusion, symptoms of knee osteoarthritis and functional capacity had a statistically significant direct effect on functional performance of knee osteoarthritis in these elderly patients. The severity of knee osteoarthritis had an indirect effect on the functional performance of knee osteoarthritis. The variance explained by these variables was 68.2% in the functional performance of knee osteoarthritis. \n Based on our study, we suggest that the first requirement for assessing functional performance in elderly patients with knee osteoarthritis is to investigate the symptoms of knee osteoarthritis and levels of functional capacity. This study will help healthcare providers to understand the structural relationships between physiological variables, and nursing interventions to improve the functional performance of elderly patients with knee osteoarthritis.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it