Blinded by emotion: Target misses follow attention capture by arousing distractors in RSVP.
Bibliographic record
Abstract
Participants are usually able to search rapid serial visual presentation (RSVP) streams and report a single target, given that RSVP distractors do not typically deplete attention required for target identification. Here, participants performed single target search, but the target was preceded by a to-be-ignored distractor varying in valence and arousal. When the critical distractor was a sexual word, lower target accuracy was observed, particularly at short distractor-target stimulus onset asynchronies, even when participants were shown the critical distractors beforehand and told to ignore them. No reduction in target accuracy was evidenced when the critical distractor was negative, positive, threatening, or emotionally neutral. Target accuracy was predicted by participants' arousal ratings to the critical distractor words and by their memory for them, but not by their valence ratings. Memory for critical distractors mediated the relationship between arousal and target accuracy. The results provide evidence that arousing sexual words involuntarily capture attention and enter awareness at the expense of goal-driven targets, at least in the context of laboratory experiments performed by young university participants for whom sexual material might have high impact and relevance.
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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 | 0.001 | 0.009 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".