Comparison of forward-facing and backward-facing tractor egress
Bibliographic record
Abstract
Falls and near-falls from tractors during ingress and egress are a health hazard that researchers should work to prevent. To gain an understanding of the factors contributing to such falls, a pilot study was completed in which kinematic analysis of tractor egress was performed using three individuals whose heights represent 5th, 50th and 95th population percentiles, respectively. The three participants were instructed to ingress and egress from the tractor. They always faced toward the tractor during ingress, however, egress involved two positions: facing toward the tractor (i.e., climbing down as one climbs down a ladder; hereafter referred to as backward facing egress or BFE) and facing away from the tractor (i.e., stepping down as one walks down a staircase; hereafter referred to as forward facing egress or FFE). Each participant completed three BFE replicates and three FFE replicates on each of the five tractors selected for this pilot study, yielding a total of 90 ingress/egress measurements. The participants’ movements were recorded with two digital video cameras to capture motion in two perpendicular planes. Kinovea motion analysis software was used to complete kinematic analysis. The observed time of descent was greater for BFE than FFE with many of the differences statistically significant at the 5% level. On average, BFE required approximately 1.4 times longer than FFE. Three-point contact was maintained 56% of the time during FFE and 68% of the time during BFE, with this difference significant at the 5% level. Maximum values for excursion of the knee joint ranged from 73 to 131° for FFE and from 44 to 111° for BFE. Although statistical analysis could not be completed because knee flexion was not visible for every step, the data suggest that the activity of FFE requires greater excursion of the knee joint than does the activity of BFE. Jumps from the bottom step to the ground were observed in 3 instances for BFE (7% of BFE trials) and in 26 instances for FFE (58% of FFE trials). Overall, it has been confirmed that kinematic analysis is able to detect differences between forward facing egress (FFE) and backward facing egress (BFE). The experimental evidence suggests that BFE is safer behaviour than FFE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".