Concussion knowledge among North American chiropractors.
Bibliographic record
Abstract
OBJECTIVES: To investigate the degree of knowledge North American chiropractors have in regards to concussion diagnosis and management. METHODS: A Concussion Knowledge Assessment Tool (CKAT) survey was administered to North American chiropractors through SurveyMonkey.com. This survey was sent to all practicing members of the American Chiropractic Association (ACA) and Canadian Chiropractic Association (CCA). RESULTS: 1321 surveys were completed and analyzed (response rate of 3.3%). The average score of the CKAT amongst North American Chiropractors was 4.82 out of 9. Using our modified scoring method, chiropractors scored 39.44 out of 48. CONCLUSIONS: North American chiropractors who participated in this study demonstrated concussion knowledge and management using the CKAT tool. Further investigation is recommended in order to address learning gaps and updating the CKAT based on current literature and guidelines.
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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 | 0.007 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".