Predicting Whole Body Vibration Exposure from Occupational Quad Bike Use in Farmers
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
Whole body vibration (WBV) exposure is recognised as a risk factor to the high prevalence of spinal musculoskeletal disorders (MSDs) experienced by farmers. The purpose of this study was to identify self-reported predictors that could be used to develop statistical models for WBV exposure (expressed as A8rms and VDV) in farmers operating agricultural quad bikes. Data were collected in the field from 130 farmers. Linear mixed effects modeling was used to determine the models of best fit. The prediction model for A8rms exposure (explaining 57% of the variance) included farmer age, estimated quad bike driving hours on day of testing and the type of quad bike rear suspension (rigid-axle rear suspension with two shock absorbers). The best model for VDV exposure (explaining 33% of the variance) included farmer age, estimated quad bike driving hours on day of testing and the type of quad bike rear suspension (rigid-axle rear suspension with two shock absorbers). In large epidemiological studies of spinal MSDs, these models would provide an acceptable indication of WBV without the costs of direct measurement.
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 | 0.001 |
| 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