Normative Data in a Sample of Canadian University Athletes Using ANAM Tests
Bibliographic record
Abstract
The baseline / postconcussion neuropsychological (NP) assessment model has been shown to be of clinical value and currently contributes significant information in sport concussion evaluation. Computerized NP batteries are now widely used in elite sport environments and are rapidly becoming more commonly utilized at the community level. With the growth of computerized NP testing, it is important to identify and understand unique characteristics with respect to baseline NP performance. The Automated Neuropsychological Assessment Metrics (ANAM) is a library of computerized NP tests designed to detect speed and accuracy of attention, memory, and thinking ability. This article describes baseline ANAM test scores in a sample of Canadian university athletes and explores the following two factors: (a) performance differences between male and female student-athletes using ANAM tests and (b) the relationship between self-reported history of concussion and baseline NP performance.
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How this classification was reachedexpand
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".