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Record W2027049748 · doi:10.3109/02699052.2013.772237

Normative data for the modified balance error scoring system in adults

2013· article· en· W2027049748 on OpenAlexaff
Grant L. Iverson, Michael S. Koehle

Bibliographic record

VenueBrain Injury · 2013
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsNormativeBalance (ability)MedicinePhysical medicine and rehabilitationTest (biology)Physical therapyPsychology

Abstract

fetched live from OpenAlex

PRIMARY OBJECTIVE: Head trauma, with or without injury to the brain, can impair balance and postural stability. The Modified Balance Error Scoring System (M-BESS) is a rapid, standardized, objective bedside test that can be helpful for monitoring recovery of balance and postural stability following head trauma. The purpose of this study is to develop preliminary normative data for this test for adults. METHODS AND PROCEDURES: Adults between the ages of 20-69 (n = 1234) were administered the M-BESS as part of a comprehensive preventive health screen. They did not have significant medical, neurological or lower extremity problems that might have an adverse effect on balance. MAIN OUTCOMES AND RESULTS: M-BESS performance significantly declined with age. Men and women performed similarly on the M-BESS. There was a small significant difference in M-BESS performance, with obese men performing more poorly than non-obese men and a larger significant difference between obese and non-obese women. CONCLUSIONS: The M-BESS normative data are presented for the total sample and by age, sex and age-by-sex. These normative data provide a frame of reference for interpreting M-BESS performance in adults who sustain traumatic brain injuries and adults with diverse neurological problems.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.062
GPT teacher head0.379
Teacher spread0.316 · 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

Citations57
Published2013
Admission routes1
Has abstractyes

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