An Eye-tracking Study of Information Sampling and Decision-making Under Stress
Bibliographic record
Abstract
The objective of this study was to probe the cognitive processing of cockpit warning displays in emergency situations by assessing the effects of acute stress on information sampling and decision-making using eye tracking equipment. A novel image-matching computer task based on the Matching Familiar Figures Task (MFFT) was designed to provide a measure of cognitive impulsivity. The stress induction procedure involved a challenging manual response task coupled with unpredictable and uncontrollable bursts of loud, aversive noise, and a matched neutral control task. Healthy participants (n=40) completed the task under two conditions: neutral and stress. Participants under stress made more image matching errors and visually sampled less in terms of both saccade count and dwell time on the MFFT, and made a greater number of responses without having first sampled all information areas displayed on the screen at least once (‘premature closure’). The findings of this study may have useful implications for the design of visual information displays across a variety of industries, particularly aviation.
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".