1.1 Extending sports concussion notions to early childhood: validity of post-concussion symptom measurement
Bibliographic record
Abstract
Objective While not typically included in consensus definitions of sports concussion, children 0–5 years are at significant risk for concussion resulting from sport and recreational activity (e.g., running, jumping) or involving sports equipment. Research in this age group critically lags behind that in older children and adolescents due to the lack of validated post-concussion symptom (PCS) measures. This study aimed to determine whether a novel, observational PCS inventory differentiates between concussion and non-concussive orthopedic injury (OI) in young children. Design Prospective, longitudinal cohort study. Setting Four North American urban pediatric Emergency Departments. Participants 156 children aged 6–72 months with either concussion or OI. Outcome Measures Report of Early Childhood Traumatic Injury Observations & Symptoms (REACTIONS) inventory, completed by a primary caregiver 10 days post-injury. Main Results 116 (53% boys, M age=35.6, SD 20.6 months) children with concussion were compared to 40 children with OI using independent sample t-tests on number of symptoms reported by their caregiver. Children with concussion consistently had more PCS than those with OI, with group differences significant across physical (t154=5.24, p<.001), cognitive (t154=3.24, p=.001) and behavioral (t154=2.06; p=.041) domains. Conclusions The results support the validity of REACTIONS for differentiating PCS from OI in early childhood. Previous work suggests that preverbal children (0–2 years) display more behavioral PCS manifestations than 3–8 year olds (Dupont et al., 2021). Developing definitions and tools that capture the unique injury characteristics of this young age group
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".