Executive functions and intraindividual variability following concussion
Bibliographic record
Abstract
UNLABELLED: The long-term outcomes of executive functions and intraindividual variability (IIV; i.e., trial-to-trial or across-task variability in cognitive performance) following concussion are unclear due to inconsistent and limited research findings, respectively. OBJECTIVE: Responding to these gaps in scientific understanding, the current study aimed to assess the utility of both executive functions and IIV at predicting concussion history. METHOD: Altogether 138 self-identified athletes (Mage = 19.9 ± 1.91 years, 60.8% female, 19.6% with one concussion, 18.1% with two or more concussions) completed three executive-related cognitive tasks (i.e., n-back, go/no-go, global-local). Ordinal logistic regression analyses examined the joint effect of person-mean and IIV as predictors of concussion status. RESULTS: Only mean response time for the global-local task predicted the number of past concussions, while no IIV variables reached unique significance. CONCLUSIONS: IIV research on concussion remains limited; however, the preliminary results do not indicate any additional value of IIV indices above mean performances at predicting past concussion. For executive functions, shifting appears most sensitive at detecting concussion group differences, with past researchers identifying post concussion impairment in attentional processing.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".