A Signal Detection Analysis of the Effects of Alcohol on Visual Contrast Sensitivity
Bibliographic record
Abstract
Numerous studies have shown that acute ethanol consumption can reduce visual contrast sensitivity when measured using traditional psychophysical methods. However, no consideration has been given to whether nonsensory factors may also play a role. The present study used both traditional techniques and signal detection procedures to evaluate this possibility. In three within-subject experiments, 41 observers (19 Females and 22 Males) were presented with faint, contrast-modulated, visual patterns and asked to say if they had seen them. In Experiment 1, contrast thresholds were measured using a randomly interleaved staircase procedure, and the data confirmed an increase in threshold following alcohol. In Experiment 2, using similar stimuli, but applying a signal detection analysis, we found that sensitivity, as reflected in d', did not change following alcohol. However, participants became more conservative in their response criterion. The third experiment was designed to allow thresholds to be measured directly with a conventional psychophysical procedure while permitting a signal detection analysis to be performed on the same data. The conventional psychophysical task showed an increase in contrast threshold, while the signal detection analysis showed no change in sensitivity, but a shift to a more conservative criterion. These data highlight the importance of taking into account alcohol's effects on cognitive processes, even when assessing basic sensory function.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".