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Record W2905074778 · doi:10.1109/lra.2018.2885197

Toward Robot-Assisted Diagnosis of Developmental Coordination Disorder

2018· article· en· W2905074778 on OpenAlexafffund
Matthew Skarsgard, Stephan C. D. Dobri, Dawa Samdup, Stephen H. Scott, T. Claire Davies

Bibliographic record

VenueIEEE Robotics and Automation Letters · 2018
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStandardizationNormativeMotor coordinationPsychologyPhysical medicine and rehabilitationSet (abstract data type)Motor functionMotor skillMedicineDevelopmental psychologyComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

Developmental coordination disorder (DCD) is a chronic neurological impairment that affects motor coordination in 5%-8% of school-aged children. Diagnostic criteria for DCD are vague and focus on ruling out other conditions, leading to a lack of standardization in DCD diagnosis. This lack of standardization makes identification of the impairment, and therefore development of interventional tools, difficult. This study was conducted to investigate a set of potential quantitative models to identify DCD based on a robotic assessment, and to compare the performance of participants with DCD to normative models of typically developed motor function. An exploratory factor analysis achieved strong differentiation between control participants and participants with DCD. This demonstrates the feasibility of a robotic assessment as a diagnostic tool for DCD.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.487

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 head0.021
GPT teacher head0.264
Teacher spread0.243 · 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 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

Citations9
Published2018
Admission routes2
Has abstractyes

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