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Record W4286566357 · doi:10.5014/ajot.2022.76s1-po208

Perceptions of Adults With Spinal Cord Injury or Disease Before and After Riding in an Autonomous Shuttle

2022· article· en· W4286566357 on OpenAlexaff
Sherrilene Classen, Justin Mason, Hannah Burns, Jordan Joseph, Emily J. Fox, E Heidi, Hannah Snyder, Lou DeMark, Carolyn Hanson

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2022
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsSheridan College
Fundersnot available
KeywordsSpinal cord injuryPsychologyMedicinePerceptionPhysical therapyPhysical medicine and rehabilitationGerontologySpinal cordPsychiatryNeuroscience

Abstract

fetched live from OpenAlex

Abstract Date Presented 04/02/2022 This study quantified changes in perceptions of adults with a spinal cord injury or disease (SCI/D) before and after an autonomous shuttle (AS) ride. Sixteen adults with an SCI/D and 16 age- and gender-matched controls completed surveys before and after a 15-minute AS ride. Perceived barriers to AS decreased after riding for both groups. Understanding perceptions regarding an AS may promote increased acceptance, adoption, and transportation equity for individuals with SCI/D. Primary Author and Speaker: Sherrilene Classen Contributing Authors: Justin Mason, Hannah Burns, Jordan Joseph, Emily Fox, Heidi E, Hannah Snyder, Lou Demark, Carolyn S. Hanson

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.292
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2022
Admission routes1
Has abstractyes

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