Focal distraction: Spatial shifts of attentional focus are not required for contingent capture.
Bibliographic record
Abstract
Contingent capture occurs when distractors that share the target's defining attribute capture attention and slow down target identification. This slowdown has been attributed to an involuntary attentional shift to the location of a pertinent distractor. The present study examined an additional source of delay: the time spent in processing pertinent distractors. In 7 experiments, distractors were presented at fixation, and targets were presented either at fixation or peripherally. Contingent capture invariably occurred when a salient distractor was presented within about 600 ms before the target, even when spatial shifts in attentional focus were ruled out. A 2-stage model is proposed in which stimuli must pass an input filter tuned to the target's defining attribute before gaining access to a high-level stage that is unavailable while a distractor is being processed.
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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 | 0.000 | 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 | 0.001 |
| 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".