Smart Home and its Use in the Occupational Therapy; With a Focus on Seniors
Bibliographic record
Abstract
Title: Smart Home and its Use in the Occupational Therapy; With a Focus on Seniors Abstract: The bachelor thesis focuses on smart home and its use in the occupational therapy. The aim of the theoretical part is to describe smart home technology in relation to people with disabilities and seniors, and to outline the role of the occupational therapist in this issue. The aim of the practical part is to assess the suitability of implementing smart home technologies in the households of selected seniors and to compile an overview of specific technologies that could address the relevant problem areas. The practical part includes five case studies, one of which serves as a model case study of a senior who already uses smart home elements in their household. The following tests and tools were used to process the case studies: the Barthel Index to assess personal activities of daily living (pADL), the Assessment of Living Skills and Resources Revised 2 for instrumental activities of daily living (iADL), the Montreal Cognitive Assessment to evaluate cognitive functions, and the Smart Evaluation Methodology of Accessibility for Home to assess the home environment. A semi-structured interview was then conducted with clients about their relationship to technology and awareness of smart home. Based on the collected data,...
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".