Discrimination of Falls and Blows in Blunt Head Trauma: Systematic Study of the Hat Brim Line Rule in Relation to Skull Fractures
Bibliographic record
Abstract
In the discrimination of falls from blows in blunt head trauma, the hat brim line rule is one of the most often used criteria. The present study assesses the validity of the hat brim line rule for skull fractures and looks at other possible criteria. All autopsy cases were retrospectively analyzed on a 5-year period. Cases selected consisted of downstairs falls (n = 13), falls from one's own height (n = 23), and homicidal blows (n = 44). Results show that fractures above the hat brim line are more in favor of blows, while fractures in the hat brim line zone are more difficult to distinguish. The majority of fractures were located on the left side for homicidal blows and on the right side for falls. A higher average number of lacerations was revealed for homicidal blows. In conclusion, this study establishes three criteria in favor of blows: (i) localization of a wound above the hat brim line; (ii) left side lateralization; and (iii) a high number of lacerations.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".