VALIDATION OF A 5-MINUTE WEB CAMERA EYE-TRACKING COGNITIVE ASSESSMENT
Bibliographic record
Abstract
Alzheimer’s disease is a form of dementia impacting memory and cognitive function in 131 million individuals worldwide. Early cognitive decline detection allows for earlier intervention, but valid and user-friendly assessment options are lacking. The purpose of this investigation was to validate a 5-minute web camera eye-tracking assessment for cognitive function. This prospective study included 49 adults (n=32 females, n=17 males; age=52.7 ± 27.3) who were divided into two age cohorts: older (ages 65+ years, n=25) and young-middle aged adults (ages 18–46 years, n=24). Of the older cohort, four had mild cognitive impairment (MCI) (Montreal Cognitive Assessment [MoCA] <26). Testing included the MoCA, NIH Toolbox cognitive assessments (Flanker Inhibitory Control and Attention, Dimensional Change Card Sort, Pattern Comparison Processing Speed [PCPS], and Picture Sequence Memory tests), Digit Symbol (DS), dual-task (habitual and fast), and 5-minute eye-tracking assessments. A Pearson’s Correlation determined relationships between the NIH Toolbox cognitive assessments and the eye-tracking test and a one-way ANOVA determined differences between cognitively intact older adults and individuals with MCI. Significant correlations (p<.05) were found for the PCPS (r=.32), DS (r=.48), and dual-task (habitual: r=.52 and fast: r=.41). The eye-tracking assessment was able to discriminate between cognitively intact adults and individuals with MCI. These results suggest the 5-minute eye-tracking assessment is a valid method for assessing cognition among adults with and without cognitive impairment. The 5-minute eye-tracking test displayed convergent validity with currently used measures of cognition, indicating it may be a widely scalable option used in place of the longer traditional testing methods.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".