A nonparametric study of the performance of cortical lesion patients on the Cognitive Assessment System
Bibliographic record
Abstract
Cortical lesion patients were tested on the Cognitive Assessment System (CAS) in the post-acute phase (median > or = 1 month) to determine the degree of sensitivity and specificity of the CAS subtests to neuropsychological impairment. Nonparametric ANOVA and subsequent Mann-Whitney statistics were used. Demographic variables of age, education, handedness, sex were controlled for Matching Numbers was sensitive to right-hemisphere lesions while Verbal-Spatial Relations was sensitive to anterior lesions. Receptive Attention and Figure Memory were sensitive to posterior lesions. Number Detection was sensitive to right anterior lesions. Nonverbal Matrices was sensitive right anterior lesions and the inclusion of a disproportionate number of left-handers within this specific group appeared to be partly moderating this effect. The magnitudes of the performance decrement for these subtests were substantial with Figure Memory demonstrating the largest effect. The results suggest that select CAS subtests could be useful for the multiple baseline assessment of neuropsychological functioning.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".