Technological Tools for Assisting People with Autism Spectrum Disorder (ASD), Intellectual Development Disorder (IDD) and Physical Disabilities (PD)
Bibliographic record
Abstract
People with an Intellectual Disability (ID), Autism Spectrum Disorder (ASD) or Physical Disability (PD) represent a significant portion of the population. Their condition leads to issues in regard to their autonomy. Living in their own home, in an autonomous way, increase the well-being of these persons and their loved ones. Assistive technologies can be seen as an interesting avenue to make that possible. However, very few researches in the field address the specific need of these persons. In this paper, we present a technological tool aiming to support these persons. We conducted a qualitative study aiming to describe the obstacles, strategies and needs for home support, as well as implementation issues and suggestions regarding assistive technology tools for people with ID, ASD and PD. We also present a new phone app that we developed according to the results of our study, which aims to support the autonomy of users and their social participation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".