Introducing the Sport Concussion Office Assessment Tool 6 (SCOAT6)
Bibliographic record
Abstract
BACKGROUND AND RATIONALESince 2004, the Concussion in Sport Group (CISG) has produced the Sport Concussion Assessment Tool (SCAT), 1 the most recent iteration of which is the SCAT6.The SCAT has greatest utility in assessing acute concussions in the first 72 hours (3 days) following injury.[2][3][4] Sportrelated concussions (SRC) are complex pathophysiological processes manifesting in varying ways across different clinical domains.Serial, multimodal clinical evaluation is recommended to identify areas for potential intervention and monitor recovery.As part of the 6th International Consensus Conference on Concussion in Sport, the author group was tasked with developing a clinical tool better suited to evaluating and managing SRC in the days and weeks after the acute (first 72 hours) period postinjury.The Sport Concussion Office Assessment Tool 6 (SCOAT6), for use in athletes 13 years and older, is the product of the 6th International Consensus Conference on Concussion in Sport aimed at assisting Health Care Professionals (HCPs) in an office-based, multimodal assessment of SRC.A child version for use in children ages 8-12 years is described separately in this issue.5 Consistent with the principles of previous consensus conference outputs, the Sport Concussion Office Assessment Tool 6 (SCOAT6) will be freely available.
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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 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.020 | 0.026 |
| Insufficient payload (model declined to judge) | 0.010 | 0.011 |
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".