The Influence of Previous Environmental History on Audio-Visual Binding Occurs during Visual-Weighted but not Auditory-Weighted Environments
Bibliographic record
Abstract
Although there is substantial evidence for the adjustment of audio-visual binding as a function of the distribution of audio-visual lag, it is not currently clear whether adjustment can take place as a function of task demands. To address this, participants took part in competitive binding paradigms whereby a temporally roving auditory stimulus was assigned to one of two visual anchors (visual-weighted; VAV), or, a temporally roving visual stimulus was assigned to one of two auditory anchors (auditory-weighted; AVA). Using a blocked design it was possible to assess the malleability of audiovisual binding as a function of both the repetition and change of paradigm. VAV performance showed sensitivity to preceding contexts, echoing previous 'repulsive' effects shown in recalibration literature. AVA performance showed no sensitivity to preceding contexts. Despite the use of identical equi-probable temporal distributions in both paradigms, data support the contention that visual contexts may be more sensitive than auditory contexts in being influenced by previous environmental history of temporal events.
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".