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- W4311800355 abstract "The visual world often presents dense and complex scenes, creating a critical need for efficient visual search—looking for targets while limiting interference from non-target distractors. Visual search is key for many professions (e.g., radiology, aviation security, military combat) and understanding the impact of distractors is key to optimizing operations. For example, assessing whether the ability to filter out distracting information is a stable difference between individuals could have important consequences for recruitment and training efforts. The goal of the current project was to simultaneously examine multiple ways in which distractors might impact search performance, necessitating a large and diverse dataset so that possible influences can be examined both in isolation and in concert with others. As such, the current project took advantage of a massive dataset (>3.8 billion trials, >15.5 million individuals) from the Airport Scanner mobile game (Kedlin Co.). The size of the dataset allows for testing multiple potential effects within the same paradigm with the same data. In the game, players serve as aviation security screeners, using their finger to tap on prohibited (targets) amongst allowed items (distractors) in simulated bags. A number of effects were explored, including the impact of featural overlap between targets and distractors on performance. For example, higher amounts of overlap between the colors of distractors and the set of possible targets caused greater interference. This and other examples of the interplay between distractor influences on search performance, such as changes in interference as exposure to individual distractors builds over experience, will be discussed." @default.
- W4311800355 created "2022-12-28" @default.
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- W4311800355 date "2022-12-05" @default.
- W4311800355 modified "2023-09-30" @default.
- W4311800355 title "Leveraging big data to disentangle effects of distractor interference and improve prediction of visual search performance" @default.
- W4311800355 doi "https://doi.org/10.1167/jov.22.14.4345" @default.
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