Neuropsychological Characterization of Cognitively-Impaired-Not-Demented (CIND) Individuals: Clinical Comparison Data
Bibliographic record
Abstract
The primary objective of the present investigation was to characterize the neuropsychological test performance of a large sample of clinic-referred individuals diagnosed as Cognitively-Impaired-Not-Demented (CIND). Participants classified as Not-Cognitively-Impaired (NCI; n = 68) differed from CIND individuals (n = 205) on a number of demographic, clinical, and neuropsychological measures. A backward stepwise logistic regression analysis revealed that measures of learning and memory, visuoconstruction abilities, and cognitive flexibility provided the best discrimination between NCI and CIND participants. Clinical comparison data for CIND participants were generated for various demographically defined groups. The amount of inter-test scatter (highest minus lowest sample-based z-score) and the overall number of cognitive impairments (impairment being defined as performance equal to or greater than 1 standard deviation below the sample mean) in CIND individuals are reported. The results support the impression that CIND is a cognitively heterogeneous condition.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".