Effects of Temporal Distribution on Utility of Temporal Factors in Competitive Audio-Visual Perceived Synchrony
Bibliographic record
Abstract
The perception of audio-visual synchrony is affected by both temporal coincidence and stimulus congruency factors. In situations when temporal and stimulus information are not in agreement, the perceiver must rely on the relative informative value of both factors in deciding which of multiple potential binding candidates are most likely to be of a common source to a target. Previous research has shown that, all being equal, participants tend to rely primarily on temporal information, and only take stimulus information into consideration when temporal information is ambiguous. The current research seeks to examine the reliance on temporal vs. stimulus information by altering the degree of useful information available in temporal aspects. By varying the temporal distribution of stimuli, it was possible to either increase or decrease the number of trials on which temporal information is conclusive. Data indicate that when temporal information is less informative (i.e., when more asynchronous stimuli are presented), we become less reliant on using prior knowledge about timing relationships when making synchrony judgements. However, when temporal information is more informative (i.e., when more synchronous stimuli are presented) there is no increase in reliance on this type of information. These findings increase what is known about competitive audiovisual processing, and the fact that temporal information serves as a kind of default stimulus property, which can be decreased by reducing the utility of that information.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".