Mass Gathering Medicine Tabletop Game - A Systems Approach to a Major Planned Event, Health Services Planning
Bibliographic record
Abstract
athletes, coaches and staff participating. These games are distinct since all athletes possess intellectual or developmental disabilities and a high prevalence of comorbidities. Methods: A prospective observational study of all patient encounters during the Games. Standardized patient encounter forms were completed by medical staff at all event venues and are reported. Results: Approximately 2,000 athletes and coaches attended and participated in 11 events over 6 days. The games were held on the University of BC campus allowing for accurate collection of all medical treatment encounters during the games. Temperatures ranged from 15-28 C (50-80 F). In total, 314 patient encounters were documented, of which 88% involved athletes. Of these, 75% were due to event related injury and 25% due to illness. There were 14 patients (5.2%) transferred to hospital for assessment and/or management, 2 via Ambulance and others via non-emergency vehicles. Track and Field competitions had the highest number of incidents of all the sporting events (29.7%), and limb extremity pain was the most common patient (chief) complaint (26.4%). Conclusion: A large scale mass participation event with athletes possessing developmental disabilities and a high prevalence of comorbidities, can be safely cared for with an appropriately designed medical support system, and not overburden local resources. This paper reviews historical injury and illness data that form the basis for planning in this population.
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 | 0.001 | 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 | 0.001 | 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".