Individual differences in ageing, cognitive status, and sex on susceptibility to the sound-induced flash illusion: A large-scale study.
Bibliographic record
Abstract
Although there is some evidence suggesting that audiovisual integration is inefficient in older adults, and that such inefficiency is associated with age-related functions such as mild cognitive impairment, falls, and balance maintenance, these associations have yet to be demonstrated in a population-representative study of ageing. Based on a sample of 3,955 adults aged over 50 years, we investigated the role of age, cognitive status, and sex on susceptibility to the sound-induced flash illusion (SIFI) as a measure of audiovisual temporal integration, while controlling for a range of covariates. We developed a hierarchical Bayesian, ordinal-regression model to determine which variables predicted audiovisual integration. Higher susceptibility to the SIFI was predicted by older age, female sex (at larger temporal asynchronies), and a lower score on the Montreal Cognitive Assessment (MoCA). Our results confirm, in a population-representative sample, that enhanced audiovisual integration is associated with ageing and extend the association between multisensory integration and mild cognitive impairment to global cognitive status. Importantly, the findings also highlight the role of the sex of the participant as a previously overlooked factor in studying multisensory perception in ageing. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".