Classic JACK modelling of driver posture and line-of-sight for operators of lift-trucks
Bibliographic record
Abstract
Several reports indicate that lift-truck (LT) drivers may be at higher risk for developing musculoskeletal injuries due to postures that must be adopted in order to manoeuvre the LT in industrial workplaces. This research uses a human simulation program to quantify changes to line-of-sight (LOS) using driving simulations acquired from actual drivers in a closed arena setting. Video files acquired during the mock-up were decimated to 3 Hz and the resulting video files were coded in 3D Match. The resulting posture file was used to drive the animation tool in Classic JACK v4.1 human simulation software while quantifying LOS with additional virtual tools. On average, the drivers adopted awkward postures with increased levels of compression in order to have less overall LOS on both LT models. The method introduced was deemed a success at simulating human motion in a virtual environment from a simple, video record of the original motion.
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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 | 0.000 | 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) | 0.001 | 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 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".