Measurement of Recovery after Traumatic Brain Injury: A Cognitive-Neuropsychological Comparison of the WAIS-R with the Cognitive Assessment System (CAS) in a Single Case of Atypical Language Lateralization
Bibliographic record
Abstract
A 20-year-old preferentially left-handed male suffered an extensive right, focal, medial, prefrontal hematoma and contusion with associated swelling, and an initially undetected progressive loss of consciousness following trauma to the forehead. Performance on the Cognitive Assessment System (CAS) at 1 and 6 months after traumatic brain injury was compared with performance on the WAIS-R at 6 months post-injury. The patient demonstrated significant residualized impairment on selected subtests of the CAS at 6 months post-injury (all ps < 0.05). The patient was also significantly impaired on the Information, Vocabulary, Arithmetic and Comprehension verbal subtests of the WAIS-R. The magnitude of these WAIS-R subtest discrepancies occurred with a low base rate (< 1%) in the WAIS-R standardization sample. In addition there was a significant VIQ versus PIQ discrepancy favouring PIQ of a magnitude occurring in less than 5% of the WAIS-R standardization sample. These findings could not be explained on the basis of any prior learning disability, poor educational opportunities, medication use, response bias, confabulation, or low level of general ability. The low scores on the verbal subtests of the WAIS-R in conjunction with the impairment on the CAS subtests are highly suggestive of lasting frontal-executive dysfunction in this patient. Incidental findings of persisting anomia, impaired processing of proverbs, acalculia, and fluctuating verbal attention, as well as impaired retrieval of verbal information in the context of intact PIQ and superior constructional praxis suggest some degree of bilateral representation of linguistic functions. The differential assessment of cognitive domains by these two instruments as well as theoretical concordance in the pattern of results is also addressed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".