Creation of an Expanded Barell Matrix to Identify Traumatic Brain Injuries of U.S. Military Members
Bibliographic record
Abstract
This paper describes the creation of a new traumatic brain injury (TBI) classification system, the Barell+ system, derived by the Center for Army Medical Department Strategic Studies. The Barell+ system is an expansion of the standard international Barell body region by nature of injury diagnosis matrix developed by the International Collaborative Effort on Injury Statistics. The expanded version (Barell+) was created as a result of a mapping effort between the original Barell matrix and the Department of Defense severity classification system used for surveillance by the Defense and Veterans Brain Injury Center (DVBIC). Starting with the Barell TBI category definitions, 19 additional TBI-related diagnosis codes from the DVBIC classification were mapped into the resulting Barell+ matrix. The new Barell+ system is compared with the original Barell matrix and the DVBIC classification system. We recommend using the TBI frequency distributions created by the Barell+ system as input data in U.S. military medical modeling and simulation efforts because it better reflects the actual distribution of TBI injuries.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".