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Record W3085709024 · doi:10.1145/3410530.3414418

SMAller aid

2020· article· en· W3085709024 on OpenAlexafffund
Amanda McLeod, Sara Nabil, Lee Jones, Audrey Girouard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIndependence (probability theory)Computer scienceRetractHuman–computer interactionWork (physics)Computer securityInternet privacyEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Individuals with mobility impairments often discuss the challenges associated with donning and doffing shirts (i.e. putting them on and taking them off). Limited previous work has tackled this issue, but the comfort and aesthetic integrity of the shirt is often forgotten. In this paper, we co-designed an adaptive shirt with individuals with mobility impairments and personal support workers. With the insights from these discussions, we developed an augmented top that transforms wide sizes (for the easy donning and doffing) into their preferred fit. The study resulted in the design of SMAller Aid, which uses Shape Memory Alloy (SMA) springs to retract to a smaller size. The shirt adapts to their needs while retaining its aesthetic integrity to empower them with independence and no required assistance.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0440.016

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 head0.114
GPT teacher head0.295
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations11
Published2020
Admission routes2
Has abstractyes

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