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Record W2015096983 · doi:10.1097/pep.0b013e3181ea8ff6

Development of a Challenge Assessment Tool for High-Functioning Children With an Acquired Brain Injury

2010· review· en· W2015096983 on OpenAlexafffund
Robyn J. Ibey, Rochelle Chung, Nicole Benjamin, Shannon Littlejohn, Andrea Sarginson, Nancy M. Salbach, Gail Kirkwood, F. Virginia Wright

Bibliographic record

VenuePediatric Physical Therapy · 2010
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of TorontoHolland Bloorview Kids Rehabilitation Hospital
FundersCanadian Institutes of Health Research
KeywordsAcquired brain injuryPsychologyTraumatic brain injuryMedicinePhysical medicine and rehabilitationNeurosciencePsychiatryRehabilitation

Abstract

fetched live from OpenAlex

PURPOSE: To develop a performance-based challenge assessment to evaluate gross motor abilities of high-functioning youth with an acquired brain injury (ABI). METHODS: Potential items were identified from the literature. A panel of 4 expert physical therapists selected items on the basis of 3 criteria: safety to test, feasibility to administer, and importance to perform. Item reduction was completed using ratings from a physical therapist web survey. The Acquired Brain Injury-Challenge Assessment (ABI-CA) was created and pilot tested with youth with an ABI. RESULTS: Seventy-eight items were identified and reduced to 47 items following expert panel discussion. Web-survey item reduction by 75 pediatric physical therapists yielded a 24-item ABI-CA that was administered to 6 youth with an ABI, aged 8 to 17 years. The ABI-CA mean score was 50.7/81.0 (SD = 17.4). CONCLUSION: The ABI-CA was feasible to administer and demonstrated gross motor activity challenges beyond the Gross Motor Function Measure. Response option refinement and measure validation are required prior to clinical/research use.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.096
GPT teacher head0.415
Teacher spread0.319 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations15
Published2010
Admission routes2
Has abstractyes

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