8.8 The functional assessment of balance in concussion (FAB-C) battery
Bibliographic record
Abstract
Objective To examine the feasibility and preliminary construct validity of a novel sports-related concussion (SRC) balance assessment battery; the Functional Assessment of Balance in Concussion (FAB-C). Design Cross-sectional study. Setting University laboratory and physiotherapy clinic. Participants Forty uninjured individuals (12 female; median age 17) and seven individuals (1 female; median age 17) who returned-to-sport after an SRC within the past 60 days. Assessment Tests for inclusion into the FAB-C were identified through a search of the evidence-base, or developed when no test existed, taking into consideration clinometric properties, dual and overlapping purposes. Participants were asked to complete three trials of the FAB-C. Outcome Measures Feasibility outcomes included battery completion, FAB-C components correlation, adverse events, cost and administration time. Construct validity was assessed by describing differences (mean±SD, median (range) or proportion (95%CI)) in the FAB-C outcomes between uninjured and concussed participants. Main Results Seven clinical tests (Balance Error Scoring System, Tandem Gait, Clinical Reaction Time [single- and dual-task conditions]), and a fit-for-purpose sport-related movement control test were included in the FAB-C. 100% of uninjured participants and 86% of concussed participants completed the entire FAB-C battery. Between component correlation coefficients were <0.7. No adverse effects were reported. The FAB-C cost was less than $100CAD with a median administration time of 49 (44–60) minutes. A greater percentage of uninjured individuals passed individual FAB-C components (range 52%-82%) compared to concussed individuals (range 17–66%). Conclusions The FAB-C demonstrated feasibility and preliminary construct validity. Further evaluation to understand reliability, concurrent and discriminant validity is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".