Is pop-out visual search attentive or preattentive? Yes!
Bibliographic record
Abstract
Is the efficiency of "pop-out" visual search impaired when attention is preempted by another task? This question has been raised in earlier experiments but has not received a satisfactory answer. To constrain the availability of attention, those experiments employed an attentional blink (AB) paradigm in which report of the second of 2 targets (T2) is impaired when it is presented shortly after the first (T1). In those experiments, T2 was a pop-out search display that remained on view until response. The main finding was that search efficiency, as indexed by the slope of the search function, was not impaired during the period of the AB. With such long displays, however, the search could be postponed until T1 had been processed, thus allowing the task to be performed with full attention. That pitfall was avoided in the present Experiment 1 by presenting the search array either until response (thus allowing a postponement strategy) or very briefly (making that strategy ineffectual). Level of performance was impaired during the period of the AB, but search efficiency was unimpaired even when the display was brief. Experiment 2 showed that visual search is indeed postponed during the period of the AB, when the array remains on view until response. These findings reveal the action of at least 2 separable mechanisms, indexed by level and efficiency of pop-out search, which are affected in different ways by the availability of attention. The Guided Search 4.0 model can account for the results in both level and efficiency.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".