Differences in the etiology of mandibular fractures in Kuwait, Canada, and Finland
Bibliographic record
Abstract
We studied causes of mandibular fractures treated in oral and maxillofacial units in three countries in years 1990-2000 in Kuwait (n=596), 1995-2000 in Canada (n=228), and 1990-99 in Finland (n=268). Of the Finnish patients, 27% were women. Corresponding percentages in Kuwait and Canada were 13 and 17%, respectively. Traffic crashes were the cause of injury in 55% of the cases in Kuwait and 33% in Oulu, but only 7% in Toronto. In Kuwait, the victims were often young people, which is why more traffic education, more control of speed, and more control of the use of safety belts should be implemented. Assault was the cause in 54% in Toronto, 12% in Kuwait, and 37% in Oulu. Falling was the cause in 22% of the cases in Kuwait. Alcohol was implicated in 21% of cases in Canada and 15% in Finland.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".