Pip and Pop
Bibliographic record
Abstract
Dynamic and complex command and control situations often require the timely recognition of changes in the environment in order to detect potentially malicious actions. Change detection can be challenging within a continually evolving scene, and particularly under multitasking conditions whereby attention is necessarily divided between several subtasks. On-screen tools can assist with detection (e.g., providing a visual record of changes, ensuring that none are overlooked), however, in a high workload environment, this may result in information overload to the detriment of the primary task. One alternative is to exploit the auditory modality as a means to support visual change detection. In the current study, we use a naval air-warfare simulation, and introduce an auditory alarm to coincide with critical visual changes (in aircraft speed/direction) on the radar. We found that participants detected a greater percentage of visual changes and were significantly quicker to detect these changes when they were accompanied by an auditory alarm than when they were not. Furthermore, participants reported that mental demand was lower in the auditory alarm condition, and this was reflected in reduced classification omissions on the primary task. Results are discussed in relation to Wickens’ multiple resource theory of attention and indicate the potential for using the auditory modality to facilitate visual change detection.
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 | 0.000 |
| 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".