The Effects of Acute Alcohol Consumption on the Visual Perception of Velocity and Direction
Bibliographic record
Abstract
The effects of alcohol on velocity and direction discrimination were examined. Participants completed both tasks under control and alcohol conditions (.08% BAC) conducted at both a “slow” (3os-1) and “fast” velocity (12os-1). Stimuli were dark dots on a light background that could vary in speed or direction. They were presented within a 5° circular field on a computer display spanning 12° × 16° in visual angle. Thresholds were measured using a Method of Constant Stimuli and a 2-interval AFC. In the velocity condition, one stimulus was always moving at the standard speed and the other, comparison, stimulus varied over a range of 85-115% of the standard velocity. Participants made judgments as to which moved faster. Using the same procedure, participants in the direction task judged which of the two drifting patterns was moving vertically. The standard was always vertical, while the comparison stimuli ranged from 0.5 to 3.5° to the right of the vertical plane. As expected, results of the velocity task demonstrated a small but significant effect of alcohol, demonstrating impairment in the general ability to accurately discriminate stimulus velocity. In the direction discrimination condition, performance was impaired at both velocities, but for the slower speed, the initial range of directions used resulted in a floor effect, with performance at chance for both the alcohol and no alcohol conditions. There was a significant effect of alcohol for the higher velocity pattern. We conclude that, overall, alcohol has a modest effect on the ability to discriminate both the velocity and the direction of moving targets.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".