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Record W7062800256

Virtual Pet Companion
\nA digital console to enhance the Experience of Children with Cerebral Palsy

2016· dissertation· en· W7062800256 on OpenAlexaffabout

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2016
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsCerebral palsyService (business)Assistive technologyRehabilitationVirtual realityVideo gameMotor area
DOInot available

Abstract

fetched live from OpenAlex

This research investigates the use of game style consoles as service technology for children with Cerebral Palsy, in order to help them develop their fine motor skills and thereby become more independent in interactions with family and caregivers. The game involves a virtual pet companion for a six-year-old child with Cerebral Palsy currently living in Toronto. It was designed specifically to cater to his interests and needs; however, this research more broadly seeks to explore the potentiality of video games for rehabilitation for children with Cerebral Palsy, taking into account the propensity and interest children often have for new technologies. Drawing from research on Cerebral Palsy, the psychology of play, existing service technologies for children with disabilities, pet therapy and gamification, my project provides insight into how new interactive technologies can afford children with Cerebral Palsy the opportunity to interact more easily with the physical world.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.014
GPT teacher head0.277
Teacher spread0.263 · 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 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

Citations0
Published2016
Admission routes2
Has abstractyes

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