Bibliographic record
Abstract
The present study pursued M. P. Bryden's legacy by investigating how contextual factors can affect laterality effects. Specifically, a cross-modal affective priming paradigm was used in two experiments to determine whether priming with facial expressions would affect responses to emotional sounds. Experiment 1 established that cross-modal priming could be obtained when presenting the emotional sounds binaurally by showing more accurate responses when prime and target were congruent than when they were incongruent, although this extended to response time only for the happy emotion. This priming effect justified Experiment 2, in which the priming paradigm was integrated into a dichotic listening task. The central finding of Experiment 2 was a congruency by ear interaction on number of correct reports, showing that presentation of a facial emotion congruent with a left target produced a large left ear advantage that was reduced when a right ear congruent prime or an incongruent pairing was used. Implications of these findings for emotion processing in the context of Bryden's legacy are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".