Systemic Lisbon Battery: Normative Data for Memory and Attention Assessments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Memory and attention are two cognitive domains pivotal for the performance of instrumental activities of daily living (IADLs). The assessment of these functions is still widely carried out with pencil-and-paper tests, which lack ecological validity. The evaluation of cognitive and memory functions while the patients are performing IADLs should contribute to the ecological validity of the evaluation process. OBJECTIVE: The objective of this study is to establish normative data from virtual reality (VR) IADLs designed to activate memory and attention functions. METHODS: A total of 243 non-clinical participants carried out a paper-and-pencil Mini-Mental State Examination (MMSE) and performed 3 VR activities: art gallery visual matching task, supermarket shopping task, and memory fruit matching game. The data (execution time and errors, and money spent in the case of the supermarket activity) was automatically generated from the app. RESULTS: Outcomes were computed using non-parametric statistics, due to non-normality of distributions. Age, academic qualifications, and computer experience all had significant effects on most measures. Normative values for different levels of these measures were defined. CONCLUSIONS: Age, academic qualifications, and computer experience should be taken into account while using our VR-based platform for cognitive assessment purposes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it