Visual-spatial perception: a comparison between instruments frequently used in the primary care setting and a computerized cognitive assessment battery
Why this work is in the frame
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Bibliographic record
Abstract
Boris Punchik,1–3 Avital Shapovalov,2 Tzvi Dwolatzky,4,5 Yan Press1–3 1Comprehensive Geriatric Assessment Unit, Clalit Health Care Services, Yassky Clinic, 2Sial Center for Research in Family Medicine, Faculty of Health Sciences, 3Community-Based Geriatric Unit, The Division of Community Health, 4Center for Multidisciplinary Research in Aging, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, 5Geriatric Unit, Rambam Health Care Campus, Haifa, Israel Background: The development of screening instruments will help the primary care team to determine when further comprehensive cognitive assessment is necessary. Design: A retrospective analysis based on medical records. Patients and setting: Patients referred to a comprehensive geriatric assessment unit. Analysis: Cognitive screening and assessment included visual-spatial components: the Mini Mental State Examination, the Clock Drawing Test, the Montreal Cognitive Assessment Test, and the Neurotrax (Mindstreams) computerized cognitive assessment battery. Results: The average age of the 190 eligible patients was 81.09±5.42 years. Comparing the individual tests with that of the visual-spatial index of Neurotrax, we found the Trail Making B test to be most sensitive (72.4%) and the Cube Test to have the highest specificity (72.8%). A combination of tests resulted in higher sensitivity and lower specificity. Conclusion: The use of a combination of visual-spatial tests for screening in neurocognitive disorders should be evaluated in further prospective studies. Keywords: visual-spatial perception, mild cognitive impairment, cognitive assessment, screening tools
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it