MemoRecall: A Senior Friendly Web Application for Holistic Intervention of Early Memory Lapses in Geriatric Individuals
Bibliographic record
Abstract
This research intends to investigate, design, and develop an online neuroenhancement tool using spaced repetition learning through games and flashcards, named MemoRecall for cognitive stimulation in geriatric patients. Pre-test and post-test assessments were done on thirty elderly participants of which three underwent pre-and-post-Montreal Cognitive Assessment (MoCA) evaluations. The analysis demonstrated marked improvement in cognition as well as effective memory stimulation with some interfaces needing refinement while adding introductory instructions was also suggested by users. The study emphasizes how MemoRecall can be used as a form of intervention, thus calling for better user guidance, optimal onboarding, and long-term research to enhance its efficacy. The functional efficiency checking of MemoRecall has shown that this platform is quite invulnerable since it possesses several features. MemoRecall appeared to be generally enjoyable for most users according to the User Experience Questionnaire (UEQ) scale. Most of the respondents agreed that it was attractive (1.678) and stimulating (1.633). The users’ preference in games suggested that Sudoku card games were still the most favored followed closely by Trivia Quizzes and Mental Math card games.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".