Moving Multisensory Research Along
Bibliographic record
Abstract
The past few years have seen a rapid growth of interest regarding how information from the different senses is combined. Historically, the majority of the research on this topic has focused on interactions in the perception of stationary stimuli, but given that the majority of stimuli in the world move, an important question concerns the extent to which principles derived from stationary stimuli also apply to moving stimuli. A key finding emerging from recent work with moving stimuli is that our perception of stimulus movement in one modality is frequently, and unavoidably, modulated by the concurrent movement of stimuli in other sensory modalities. Visual motion has a particularly strong influence on the perception of auditory and tactile motion. These behavioral results are now being complemented by the results of neuroimaging studies that have pointed out the existence of both modality-specific motion-processing areas and areas involved in processing motion in more than one sense. The challenge for the future will be to develop novel experimental paradigms that can integrate behavioral and neuroscientific approaches in order to refine our understanding of multisensory contributions to the perception of movement.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.021 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".