Bibliographic record
Abstract
In 1998 there were 362 drowning fatalities in Canada. Of these, 30 % involved recreational boating. 1 One half of all recreational boating drownings involve small open power boats (shorter than 5.5m) and canoes. 1 The vast majority of incidents involved males between 16 and 54 years of age with a peak period between 25-45 years. 2 Interestingly, an examination of these recreational boating fatalities shows that only 14 % of those who drowned were identified as nonswimmers. 1 Clearly, increasing boaters ' experience in the water, and level of swimming ability are not the only or necessarily best ways to reduce the incidence of recreational boating-related drowning. Lifejacket/PFD Use One alternative approach is to encourage the wearing of buoyant gear to keep a person afloat after they've left a boat involuntarily. While there is little doubt of the efficacy of lifejackets or personal floatation devices (PFDs) in keeping someone afloat, there is little evidence that they are, in fact, being worn by the group at-risk. A national observational study undertaken by the Coast Guard
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".