Correlation of quantitative ultrasound measurements with material properties and bone mineral density in the equine metacarpus
Bibliographic record
Abstract
Abstract This study explored the relationship between speed-of-sound (SOS) measurements and the material properties of metacarpal bones in order to validate a device that uses linear unicortical transmission of ultrasound. SOS, ultimate tensile strength and modulus of elasticity were determined at nine experimental sites. Measurements of SOS and bone mineral density were collected at three of the nine experimental sites. Twenty-five equine metacarpal (MC3) bones were used. Micro-computerized tomography was used to validate testing protocols. SOS measurements were highly site- and horse-dependent. One or more statistically significant correlations were found with ultimate tensile strength, modulus of elasticity and bone mineral density in four of the nine experimental sites. A previously described pattern of high lateral and medial cortical stiffness and SOS was found in the mid-diaphysis that correlated with bone mineral density ( r 2 =0.25, P <0.01) and modulus of elasticity ( r 2 =0.14, P <0.05). SOS and ultimate tensile strength correlated strongly in the distal dorsal metacarpus ( r 2 =0.47, P <0.001). Lateral and medial distal-level sites just above the fetlock joint had a variable amount of cancellous bone, reducing the ultimate strength of these sites. The study indicates that quantitative ultrasound is sensitive to differences in the quality of equine metacarpal bone, so this technique may be useful for monitoring adaptation to exercise and bone development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".