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Record W139700982

Redesign of the rollator's (walker's) parking brake system

2008· article· en· W139700982 on OpenAlexaff
Stephen Siu, Maria Wong, Aditya Shah, Heng Li, Alan Soong, Ray Cao, Lou Pino, John Zelek

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLock (firearm)BrakeForgettingMechanism (biology)Computer scienceAutomotive engineeringPsychologyEngineeringCognitive psychologyMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

A large concern for the elderly is forgetting to engage the parking mechanism on the rollator (i.e., walker) before using it as a seat or for support. Interviews and research indicate that the elderly are prone to falling because of the dependence on memory to activate the rollator's parking mechanism and also the inability of the current rollator to effectively park when the braking mechanism is engaged. We focus on creating a rollator that will brake by default and thus will eliminate the need for users to rely on memory to activate the parking mechanism. The first iteration of our design is based on the concept of a pin-lock braking system that is activated by the top frame of the rollator. The second and final iteration of the design replaces the pin-lock with a chain-lock. Based on another round of customer feedback, the next generation of the rollator will replace the chain-lock with a ratchet gear lock.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.183
Teacher spread0.165 · 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 designBench or experimental
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

Citations2
Published2008
Admission routes1
Has abstractyes

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