Tracking neuropsychological recovery following concussion in sport
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PRIMARY OBJECTIVE: The purpose of this study was to illustrate the serial use of computerized neuropsychological screening with ImPACT to monitor recovery in a clinical case series of injured athletes. METHODS AND PROCEDURES: Amateur athletes with concussions (n= 30, average age= 16.1, SD= 2.1 years) underwent pre-season testing and three post-concussion evaluations within the following intervals: 1-2 days, 3-7 days (M= 5.2 days) and 1-3 weeks (M= 10.3 days). The study selection criteria increased the probability of including athletes with slow recovery. RESULTS: Repeated measures ANOVAs revealed significant main effects for all five composite scores (verbal memory, visual memory, reaction time, processing speed and total symptoms). In group analyses, performance decrements and symptoms relating to concussion appeared to largely resolve by 5 days post-injury and fully resolve by 10 days. Athletes' scores were examined individually using the reliable change methodology. At 1 day post-injury, 90% had two or more reliable declines in performance or increases in symptom reporting. At 10 days, 37% were still showing two or more reliable changes from pre-season levels. CONCLUSIONS: This study illustrates the importance of analysing individual athletes' test data because group analyses can obscure slow recovery in a substantial minority of athletes.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it