The integrity of the corpus callosum in individuals following mild head injury
Bibliographic record
Abstract
Moderate and severe traumatic brain injury can produce diffuse axonal injury (DAI), which often includes damage to the corpus callosum. It is not clear, however, whether callosal dysfunction can also occur in cases of mild traumatic brain injury (MTBI). Right-handed adults (18--79 years old), including 21 survivors of a MTBI (18 women) (occurring within five years of the start of this study) and 21 uninjured controls (17 women) volunteered. Baseline measures consisted of the Lethbridge Neuropsychological Battery and several other cognitive tests, including the WAIS-III. I used several tasks to measure the integrity of the interhemispheric transfer of auditory, visual, and somatosensory information via the corpus callosum (Dichotic Listening, Fused Words, a series of Tachistoscope (T-Scope Tasks), and Haptic). Both groups showed a right ear advantage on the Dichotic Listening and Fused Words Tasks. Performances on all callosal tests were similar for both groups with the following exceptions: T-Scope Matching Task latency, T-Scope Verbal Color Discrimination Task accuracy, and Haptic Task latency. The MTBI group was significantly slower than the Control group when using their right hand to respond to stimuli presented to the left visual field on the T-Scope Matching Task. When using their left hands to respond, however, both groups were less accurate during the non-transfer than the transfer conditions. Further, the Control group was significantly slower at responding on the non-transfer than the transfer conditions of this task. The MTBI group was significantly less accurate in verbally stating if two disks were the same or different in color on the Verbal Color Discrimination Task. Finally, the MTBI group was significantly slower than Controls in identifying shapes on the Haptic Task. These findings suggest corpus callosum dysfunction might occur even after a single MTBI, however, the most persistent symptom may be an increase in the crossed-uncrossed difference during tactile information transfer.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".