Concussion in competitive cycling. A call for discipline-specific diagnostic frameworks
Bibliographic record
Abstract
Results• Competitive cycling consists of ten broad cycling disciplines which break down into 40 sub-disciplines all of which are governed by the World Body for Cycling, the Union Cycliste Internationale (UCI)• The UCI acknowledges the lack of epidemiological research within its Agenda 2030 and aims to "promote and support research in cycling epidemiology and medicine, especially for the benefit of lesser-known disciplines".[1] • The UCI published a Sports-related concussion (SRC) guidance document in 2020.However, SRC remains a much-debated diagnostic challenge for cycling.[2,3] • The first International Olympic Committee Consensus statement for reporting injuries and illness in cycling was published in 2021.[4,5] • This systematic review aims to comprehensively analyse and synthesise the existing literature on cycling-related injuries and illness across all competitive disciplines.Design: Systematic epidemiological review and meta-analysis.
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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 | 0.018 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".