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Record W2263711634 · doi:10.1177/2055668315594076

Development of an integrated staircase lift for home access

2015· article· en· W2263711634 on OpenAlexafffund
Johanne Mattie, Jaimie Borisoff, Danny Leland, William C. Miller

Bibliographic record

VenueJournal of Rehabilitation and Assistive Technologies Engineering · 2015
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British ColumbiaBritish Columbia Institute of Technology
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsLift (data mining)StairsComputer scienceProcess (computing)Human–computer interactionEngineeringCivil engineering

Abstract

fetched live from OpenAlex

PURPOSE: Stairways into buildings present a significant environmental barrier for those with mobility impairments, including older adults. A number of home access solutions that allow users to safely enter and exit the home exist, however these all have some limitations. The purpose of this work was to develop a novel, inclusive home access solution that integrates a staircase and a lift into one device. METHOD: The development of an integrated staircase lift followed a structured protocol with stakeholders providing feedback at various stages in the design process, consistent with rehabilitation engineering design methods. RESULTS: A novel home access device was developed. The integrated staircase-lift has the following features: inclusivity, by a universal design that provides an option for either use of stairs or a lift; constant availability, with a lift platform always ready for use on either level; and potential aesthetic advantages when integrating the device into an existing home. The potential also exists for emergency descent during a power outage, and self-powered versions. CONCLUSIONS: By engaging stakeholders in a user centred design process, insight on the limitations of existing home access solutions and specific feedback on our design guided development of a novel home access device.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.708
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.082
GPT teacher head0.418
Teacher spread0.336 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

Explore more

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