Exploiting the Auditory Modality in Decision Support
Bibliographic record
Abstract
The rate at which technology continues to develop and permeate our lives is such that it has become increasingly easier, and thus more likely, for information to be presented to us via different modalities simultaneously. But to what extent does this confluence of information affect our subsequent judgment and performance? Furthermore, what are the implications for system design when this information is critical to saving our lives and others? This study uses a visual ‘microworld’ simulation of a naval anti-air warfare to investigate whether the content and priority of audio messages that accompany changes in the visual modality assist or hinder performance in the task (identification of change and evaluation of threats). Results indicate that although helping critical change detection, a critical warning in the auditory modality is not as efficient as its visual counterpart. Moreover, audio messages tended to bias threat evaluation towards perceiving objects as more hostile than they were in reality. Such findings have clear implications in regard to the costs and benefits of further exploiting the auditory modality in dynamic visual environments.
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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 | 0.000 |
| 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".