Age differences in visual statistical learning.
Bibliographic record
Abstract
Recent work has shown that older adults' lessened inhibitory control leads them to inadvertently bind co-occurring targets and distractors. Although this hyper-binding effect may lead to the formation of more superfluous associations, and thus greater interference at retrieval for older adults, it may also lead to a greater knowledge of information contained within the periphery of awareness. On the basis of evidence that younger adults only show learning for statistical regularities contained within attended information, we asked whether older adults may also show learning for regularities contained within to-be-ignored information. Older and younger adults viewed a series of red and green pictures and performed a 1-back task on one of the colors. Unbeknownst to participants, both color streams were organized into triplets that occurred sequentially. Implicit memory for the triplets from both the attended and ignored streams was tested using a speeded detection task. Replicating previous work, younger adults demonstrated more learning for the attended triplets than the unattended triplets. Older adults, however, demonstrated similar learning for both the attended and ignored triplets, suggesting that contrary to popular belief, they may actually know more than younger adults about the world around them, including how seemingly irrelevant events co-occur.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".