Imaging of rib stress fractures in elite rowers: the promise of ultrasound?
Bibliographic record
Abstract
Stress fractures are common injuries in endurance athletes, and are due to high-intensity, repetitive training activities.1 ,2 Although these fractures occur more frequently in weight-bearing bones, the ribs are a common site for non-weight-bearing stress fractures.3 Rib stress fractures are the most common type of stress fracture in rowers, with an incidence that has been reported as being between 6.1% and 12%.2–5 This relatively large range of estimated incidence rates is likely due to both under-reporting and underdiagnosis of rib stress fractures, as well as an overall lack of epidemiological studies on musculoskeletal injury rates in rowers.3 4 6 For these reasons, the burden of rib stress fractures is likely higher than the literature suggests.3 7 In fact, there is so little epidemiological data available that some recommendations suggest that focal rib pain in any elite rower should be regarded as a stress fracture until proven otherwise.8 Rib stress fractures are of great concern to elite-level rowers and their teams. Rib-related injuries account for the most time lost from training and competition, which can have a negative impact on the affected rower, and on crew members and coaches.3 6 8 Furthermore, because injuries can require up to 6–8 weeks of rest, a rib stress fracture can be a season-ending injury at the elite level.8 This is especially worrisome because a stress fracture that occurs during training for a major championship could prevent the injured athlete from competing altogether.3 Finally, elite level athletes may be more reluctant to abstain from training, and training despite a suspected rib stress fracture may lead to even more serious injury such as a displaced fracture and greater time lost from sport.8–10 Much like stress fractures in weight-bearing bones, rib stress fractures are thought to result from …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".