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Record W2026631677 · doi:10.1352/2326-6988-01.02.121

Navigation Between Menu Screens and Multiple Touch Points on a Touch Screen Tablet to Access and Complete Multi-Step Tasks Using Video Prompting

2013· article· en· W2026631677 on OpenAlexaff
Linda C. Mechling, Ashley M. Foster, Kevin M. Ayres

Bibliographic record

VenueInclusion · 2013
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsComputer sciencePoint (geometry)MultimediaHuman–computer interactionVideo recording

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the capacity of three young adults with intellectual disability to independently operate a touch screen tablet, including examining their ability to navigate between three different menu screens, each with four different touch point options (branching and to access and complete multi-step tasks using video prompting. A multiple probe across subjects design was used and data were collected on these young adults' abilities to navigate between screens and perform steps for becoming more independent in cooking, cleaning, and folding tasks. All three participants learned to navigate between different menu screens, access different video programs, complete the multi-step tasks, and maintained skill performance from 10 to 61 days.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0020.001

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 head0.132
GPT teacher head0.362
Teacher spread0.231 · 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 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

Citations7
Published2013
Admission routes1
Has abstractyes

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