Are Age-Related Differences Uniform Across Different Inhibitory Functions?
Bibliographic record
Abstract
OBJECTIVES: In the current experiment, we examined the relative age-sensitivity of 3 inhibitory functions: access, deletion, and restraint by taking into consideration their underlying control processes: proactive and reactive control. METHODS: The 3 inhibitory functions were measured using a sequential flanker task. Young (age: 18-35, n = 24) and older adults (age: 60-75, n = 25) first memorized a series of 8 animal words in a fixed order. In the test phase, these stimuli were presented randomly either singly or with flankers and participants responded "yes" or "no" based on the prelearned sequence. In the access trials, flankers were either ahead of the current target or unrelated. In the deletion trials, flankers were previous target items. In the restraint trials, the flanker cues (XXXX) prompted the participants to withhold responses occasionally. Unflanked trials served as the baseline condition. RESULTS: Age-related differences in the magnitude of inhibition effects were largest in restraint, followed by deletion. No age-related differences were observed in access. DISCUSSION: Our findings suggest that the magnitude of age-related differences in inhibitory functions is contingent on the degree of proactive control recruited by a given inhibitory function.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".