Patterns of fatal machine rollovers in Canadian agriculture
Bibliographic record
Abstract
INTRODUCTION: Our objectives were to examine the activities and circumstances associated with agricultural machine-related rollover fatalities. METHODS: We identified agricultural machine rollover fatalities recorded by the Canadian Agricultural Injury Surveillance Program (CAISP) in 1990-2005. We determined sideways and backwards rollovers by year, age and sex of the victims, agricultural season, machine type, and the activity, circumstances and location of the injury event. RESULTS: The annual rate of rollover fatalities in Canada was 9.1 per 100,000 farm operations. Rollover fatalities decreased to 30% of baseline over the 16-year study period (p = .004). Fatal rollovers most often occurred among men aged 50-69 years and 60-79 years for sideways and backwards rollovers, respectively. DISCUSSION: Sideways rollovers occur when driving across an incline or at the edge of a ditch bordering a roadway or field. Backwards rollovers occur when driving up an incline, towing or extracting stuck machines, pulling stumps or trees, and towing implements or logs. Primary prevention programs for rollover injuries should target these identified patterns of injury.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".