Analysis of the influence of independent variables used for reconstruction of a traumatic brain injury incident
Bibliographic record
Abstract
Traumatic brain injuries contribute to a high degree of morbidity and mortality in society. To study traumatic brain injuries researchers reconstruct the event using both physical and FE models. The purpose of these reconstructions is to correlate the brain deformation metric to the type of injury as a measure for prediction. These reconstructions are guided by a series of independent variables which all have influence upon the outcome variables. This research uses a combination of physical and FE modelling to quantify how independent variables such as velocity and impact vector (angle) contribute to the resulting variance in brain deformation metrics. The results indicated that using a Hybrid III neck controls the rotational acceleration response from an impact. Also, it was found that strain rate and product of strain and strain rate were more sensitive to changes in impact angle. Linear acceleration decreased with increasing impact angle, while brain deformations did not follow this trend, which suggests that peak linear acceleration may not be the only factor in the production of larger brain deformations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".