Survey of injury sources for a trampoline with equipment hazards designed out
Bibliographic record
Abstract
AIM: In Australia, trampolines contribute approximately one-quarter of all childhood play-equipment injuries. The purpose of this study was to gather and evaluate injury data from a nontraditional, 'soft-edged', consumer trampoline in which the equipment injury sources have been designed out. METHODS: A survey was undertaken in Queensland and New South Wales. The manufacturer of the nontraditional trampoline provided the University of Technology, Sydney, with their Australian customer database. Injury data were gathered in a pilot study by phone interview, then in a full study through an email survey. Results from 3817 respondents were compared with earlier Australian and US data from traditional trampolines gathered from emergency departments. RESULTS: A significantly lower proportion of the injuries caused by falling off or striking the equipment was found for this new design when compared with traditional trampolines both in Australia and in the USA. The age of children being injured on trampolines in Australia was found to be markedly lower than in North America. CONCLUSIONS: This research indicates that with appropriate design the more severe injuries on traditional trampolines can be significantly reduced.
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.
How this classification was reachedexpand
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 | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".