Training Load Capacity, Cumulative Risk, and Bone Stress Injuries: A Narrative Review of a Holistic Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bone stress injuries (BSIs) are a common orthopedic injury with short-term, and potentially long-term, effects. Training load capacity, influenced by risk factors, plays a critical role in the occurrence of BSIs. Many factors determine how one's body responds to repetitive loads that have the potential to increase the risk of a BSI. As a scientific community, we have identified numerous isolated BSI risk factors. However, we have not adequately analyzed the integrative, holistic, and cumulative nature of the risk factors, which is essential to determine an individual's specific capacity. In this narrative review, we advocate for a personalized approach to monitor training load so that individuals can optimize their health and performance. We define "cumulative risk profile" as a subjective clinical determination of the number of risk factors with thoughtful consideration of their interaction and propose that athletes have their own cumulative risk profile that influences their capacity to withstand specific training loads. In our narrative review, we outline BSI risk factors, discuss the relationship between BSIs and training load, highlight the importance of individualizing training load, and emphasize the use of a holistic assessment as a training load guide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 |
| 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 it