Congruency, attentional set, and laterality effects with emotional words.
Bibliographic record
Abstract
The present study investigated the influence of attention and word-emotion congruency on auditory asymmetries with stimuli that include verbal and emotional components. Words were presented dichotically to 80 participants and were pronounced in either congruent or incongruent emotional tones. Participants were asked to identify the presence of a target word or emotion under 1 of 2 conditions. The blocked condition required detection of a word or emotional target in separate blocks. In the randomized condition, the target was changed across trials by means of a postcue. A right-ear advantage (REA) and a left-ear advantage (LEA) were found for word and emotion targets, respectively. However, the finding of a Condition x Stimulus Type x Ear x Congruency interaction indicated that in the randomized condition, a REA was obtained for words when the stimuli were congruent and a LEA was observed for emotions when the stimuli were incongruent. The findings suggest that randomizing the target reduced the influence of the attentional set established by blocking the target. It is likely that this promoted the detection of hemispheric interference in the randomized condition.
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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 | 0.007 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".