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
BACKGROUND: Manually repositioning patients puts healthcare providers at risk for injury; this may be reduced by using low-friction bedsheets. OBJECTIVES: The aim of this study was to evaluate the physical properties and the physiological measures of muscle activity and perceptual participant accounts between a new slider sheet system and traditional hospital bedsheet makeup (soaker pad with a jersey bottom sheet). METHOD: Surface electromyography was recorded from the arm and shoulder muscles of five healthcare providers executing a patient repositioning (boosting and turning) in a controlled laboratory setting to gain an indication of muscle activity required for two types of bedsheets (slider system and traditional sheet makeup). The Borg Scale was used to establish rating of perceived exertion for these repositioning tasks on the two types of bedsheet makeup. To evaluate the sheets independent of human interaction and contact, the physical resistive characteristics of the sheets were calculated by determining the coefficient of friction. RESULTS: Patient repositioning on traditional sheets, compared with the slider system, resulted in 16% greater electromyography burst numbers and 11% longer duration for both boosting and turning. Moreover, ratings of perceived exertion for repositioning patients on traditional sheets versus on slider sheets were more than double. The coefficient of friction of the traditional sheets was 65% less in the slider sheet system. DISCUSSION: This study suggests that manually repositioning patients on a low-friction slider system reduces muscular and perceived effort. Proper usage of this type of bedsheets may reduce the risks associated with musculoskeletal strain and injuries of the healthcare providers.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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