Leg Tissue Mass Composition Affects Tibial Acceleration Response Following Impact
Bibliographic record
Abstract
To date, there has not been a direct examination of the effect that tissue composition (lean mass/muscle, fat mass, bone mineral content) differences between males and females has on how the tibia responds to impacts similar to those seen during running. To evaluate this, controlled heel impacts were imparted to 36 participants (6 M and 6 F in each of low, medium and high percent body fat [BF] groups) using a human pendulum. A skin-mounted accelerometer medial to the tibial tuberosity was used to determine the tibial response parameters (peak acceleration, acceleration slope and time to peak acceleration). There were no consistent effects of BF or specific tissue masses on the un-normalized tibial response parameters. However, females experienced 25% greater peak acceleration than males. When normalized to lean mass, wobbling mass, and bone mineral content, females experienced 50%, 62% and 70% greater peak acceleration, respectively, per gram of tissue than males. Higher magnitudes of lean mass and bone mass significantly contributed to decreased acceleration responses in general.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".