Evaluation of the effects of ethanol on static and dynamic gait.
Bibliographic record
Abstract
OBJECTIVE: We used two balance assessment devices, computerized dynamic posturography (CDP) and Swaystar transducers to detect subtle balance system deficits in nine subjects who had ingested minimal amounts of alcohol. DESIGN: Nine subjects were evaluated with both modalities before, and repetitively after, ingesting a small amount of alcohol. METHODS: We measured condition 5 (sway referenced platform; eyes closed) on CDP and tandem walking with eyes closed while wearing Swaystar to see if either test could detect a balance deficit. MAIN OUTCOME MEASURES: We measured total sway amplitude with eyes closed in pitch and roll planes during tandem walking with Swaystar, and static balance scores of CDP sensory organization testing condition 5 before and after alcohol ingestion at 20 min intervals. RESULTS: Although there was no detectable deficit measurable by CDP, eight of our nine subjects showed increased dynamic sway as measured by Swaystar, after alcohol ingestion. Total sway was significantly greater (p=.05) after alcohol ingestion. CONCLUSION: It is important to assess dynamic, rather than static, equilibrium as it may have potential in detecting very subtle balance deficits.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".