Methods for mitigating the vigilance decrement in an auditory sonar monitoring task: A research synthesis
Bibliographic record
Abstract
Sustained attention or operator vigilance is required in the detection o f critical signals that occur infrequently and at irregular intervals over a prolonged period.In this paper, we review some methods for mitigating the vigilance decrement for an auditory sonar monitoring task.These methods pertain to enhancing the saliency o f sonar targets for situations when the operator may be required to monitor multiple displays, listen to competing sound sources, attend to distractions, and cope with ambient noise.Enhanced target saliency is expected to assist in maintaining operator efficiency via increasing detection rate and decreasing detection latency o f auditory sonar targets.This should lead to tactical superiority of sonar operators in the continuing threat o f underwater warfare. s o m m a ir eIl est ncessaire que l 'oprateur fasse preuve d 'une attention ou d'une vigilance soutenues pour dtecter les signaux critiques qui se produisent peu frquemment et des intervalles irrguliers sur une priode prolon ge.Le prsent document examine certaines des mthodes permettant d 'attnuer la baisse de vigilance durant une tche auditive de surveillance sonar.Ces mthodes mettent en vidence des cibles sonar dans des situa tions o l 'oprateur doit surveiller plusieurs affichages et prter l 'oreille des sources sonores conflictuelles alors qu'il est expos des distractions et du bruit ambiant.La mise en vidence des cibles devrait aider maintenir l 'efficacit de l 'oprateur en augmentant le taux de dtection et en diminuant la latence de dtec tion des cibles sonar durant une tche auditive.Il devrait en rsulter une supriorit tactique de l 'oprateur sonar dans la menace permanente de la guerre sous-marine.
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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 | 0.003 | 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".