MétaCan
Menu
Back to cohort
Record W4205490240 · doi:10.3109/17483107.2010.509885

Design of built environments to accommodate mobility scooter users: part I

2010· article· en· W4205490240 on OpenAlexaff
Tilak Dutta, Emily C. King, P. J. Holliday, Susan M. Gorski, Geoff Fernie

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2010
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsComputer scienceHuman–computer interactionTransport engineeringArchitectural engineeringEngineering

Abstract

fetched live from OpenAlex

PURPOSE: To determine the minimum dimensions needed to allow five models of powered mobility scooters to manoeuvre within five commonly encountered indoor spatial configurations. METHOD: We measured manoeuvrability of five scooters judged by their manufacturers to have a good combination of indoor mobility and outdoor performance (including in rural environments). We determined the minimum space needed to manoeuvre the scooters through the following five spatial configurations: turning 180° in a corridor, performing U-turns around 50 mm (2″) and 1200 mm (4') obstacles, turning 90° from a doorway and approaching a counter or work surface from the side. Free-standing styrofoam walls were used to define each configuration. An expert driver repeatedly manoeuvred the scooters through each configuration while we incrementally decreased the dimension of interest until it was no longer possible to complete the manoeuvre. Each scooter's turning diameter was also measured and compared to the manufacturer's specification. RESULTS: Minimum space requirements for each scooter for five spatial configurations are given and compared to existing standards. CONCLUSIONS: None of the scooters tested were capable of completing all manoeuvres within the space allowed by existing standards. These findings will contribute to recommendations for new standards for built environments that can accommodate scooter users.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.394
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueDisability and Rehabilitation Assistive TechnologySame topicAssistive Technology in Communication and MobilityFrench-language works237,207