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Record W4386209697 · doi:10.3233/shti230652

A Novel Geospatial Assistive Navigation Technology for Seamless Multimodal Mobility of Wheelchair Users

2023· article· en· W4386209697 on OpenAlexaff
Mohamed Bahloul, Normand Boucher, François Routhier

Bibliographic record

VenueStudies in health technology and informatics · 2023
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsWheelchairGeospatial analysisAssistive technologyPerceptionComputer scienceSocial acceptanceHuman–computer interactionTransport engineeringWorld Wide WebEngineeringPsychologyGeographyCartography

Abstract

fetched live from OpenAlex

Mobility is fundamental for social participation of people with disabilities. Unfortunately, traditional design of urban environments, including infrastructure and services are developed based largely on a standard perception of an independent, fully functional citizen without disability which limits the mobility social participation of PWD. This paper presents the design and development of a novel geospatial assistive navigation technology to support multimodal mobility of people with disabilities, especially those using manual wheelchair in urban areas.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.344
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2023
Admission routes1
Has abstractyes

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