Rejecting familiar distracters during recognition in young adults with traumatic brain injury and in healthy older adults
Bibliographic record
Abstract
The most common cognitive complaint reported by healthy older adults and young adults with traumatic brain injury (TBI) is memory difficulties. We investigated the effects of normal aging and the long-term effects of TBI in young adults on the susceptibility to incorrectly endorse distracter information on a memory test. Prior to a study phase, participants viewed a "pre-exposure" list containing distracter words, presented once or three times, and half of the target study words. Subsequently, during the study phase, all target words were presented such that, across lists, study words were viewed either once or three times. On the recognition test, TBI and older adult participants were more likely to falsely endorse "pre-exposed" distracter words viewed three times as being from the target study list, compared to non-head-injured young controls. Normal aging and head injury in young may similarly compromise one's ability to reject highly familiar, but distracting, information during recognition. Older adult and TBI participants were also slower to complete the Trail Making task and had poorer output on a Digit Span task, suggesting these two populations share a deficit in executive function and working memory. Similar changes in frontal lobe function may underlie these shared cognitive deficits.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".