Bibliographic record
Abstract
Past research has shown, separately, that endogenous location cues and high perceptual load search tasks increase the specificity of attentional deployment to task-relevant regions of the visual field, while complex task-irrelevant backgrounds greatly resembling task-relevant stimuli reduce it. Here, we investigated in the same study whether the perceptual load created by an endogenously cued set of task-relevant stimuli determines whether a surrounding complex background of similar task-irrelevant stimuli would interfere with search. Our results show that high perceptual load protects against interference from a complex background of similar but task-irrelevant stimuli, situated just beyond the boundaries of the task-relevant set. Furthermore, our findings demonstrate that search characteristics do not change when the relevant set is restricted attentionally to a smaller delineated area, even in the presence of a background. Finally, we found that the efficacy of endogenous location cueing is not dependent on the type of search task that occurs in the cued area. Our findings also reveal that alternative attention-directing strategies, such as guided search and signal detection, may be employed in such tasks in the absence of endogenous location cueing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".