Concussion knowledge among Sport Chiropractic Fellows from the Royal College of Chiropractic Sports Sciences (Canada).
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to investigate the degree of knowledge that sports chiropractors have in regard to concussion diagnosis and management. METHODS: A concussion knowledge survey was administered to Sport Chiropractic Fellows of the Royal College of Chiropractic Sports Sciences - Canada (RCCSS(C)) (n=44) via SurveyMonkey.com. RESULTS: Sports chiropractors scored statistically higher on the survey when compared to chiropractic residents (mean =5.57 vs. 5.25; t=2.12; p=0.04) and to fourth year chiropractic interns (mean = 5.57 vs 5.2; t=2.45; p=0.02). Additionally, with our modified scoring, the sports chiropractors scored 85.3%. A few knowledge gaps were identified in the sample population. CONCLUSION: Sports chiropractors demonstrated the skills and knowledge to diagnose concussion and excel at identifying the definition and mechanism of concussion, but knowledge gaps regarding diagnosis and management of concussion were found in the sample population.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".