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Record W2909817141 · doi:10.1055/s-0038-1676451

Clinical Assessments of Balance in Adults with Concussion: An Update

2019· review· en· W2909817141 on OpenAlexaff
Rebecca J. Reed-Jones, Brian Székely, Douglas W. Powell, Nicholas G. Murray

Bibliographic record

VenueSeminars in Speech and Language · 2019
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsConcussionBalance (ability)MedicineMEDLINEPhysical medicine and rehabilitationPsychologyInjury preventionPoison controlMedical emergencyChemistry

Abstract

fetched live from OpenAlex

Postural instability is a cardinal indicator of concussion. Assessments of the postural control system range from clinical to laboratory tests that assess the balance of the individual. In a previous article regarding clinical assessment of balance in adults with concussion, we reviewed the importance of balance as a component in concussion evaluations. The purpose of this review article is to update the information previously published in 2014. Since 2014, research has provided evidence for the incorporation of dynamic methods for evaluating balance postconcussion with particular emphasis on sensory system integration and dual tasking. Therefore, this review will examine the current state of knowledge on how concussion injuries affect postural control, advancements in evaluating balance postconcussion, such as novel eye-tracking techniques, and current recommendations for best practices for balance assessment.

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)0.002
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0050.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.068
GPT teacher head0.465
Teacher spread0.397 · 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 designSystematic review
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

Citations9
Published2019
Admission routes1
Has abstractyes

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