Introducing the Concussion Recognition Tool 6 (CRT6)
Bibliographic record
Abstract
What's new? ⇒ Continuity across the Sport Concussion Assessment Tool 6 (SCAT6), Child SCAT6 and the Concussion Recognition Tool 6 (CRT6).⇒ Emphasis that the CRT6 is NOT a tool for diagnosing concussion.⇒ Enhanced emphasis on Recognise and Remove, including para athletes.⇒ Further expansion of the Red Flags section, including instruction that the presence of any red flag demands removal from activity and urgent medical attention.⇒ Warning not to remove helmets unless trained to do so.⇒ Emphasis on assuming the possibility of spinal injury with any head injury.⇒ List of visible clues/signs of suspected concussion and symptoms consistent with the SCAT6/Child SCAT6.⇒ Symptom list is divided into three symptom categories (physical symptoms, changes in emotions and changes in thinking) for easier recognition of sport-related concussion.⇒ Example of 'awareness' questions expanded for use across a greater number of sports.⇒ Emphasis added on explicit instructions that any athlete suspected of concussion should be immediately removed from activity and not returned to activity until assessed and managed medically.⇒ Cautions regarding acute management and restrictions on behaviours for any athlete with a suspected concussion (eg, not being alone, drinking alcohol, driving or using recreational drugs).
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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 | 0.015 | 0.053 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.026 | 0.028 |
| Insufficient payload (model declined to judge) | 0.019 | 0.019 |
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".